Data processing systems and methods for integrating privacy information management systems with data loss prevention tools or other tools for privacy design

ABSTRACT

Computer implemented methods, according to various embodiments, comprise: (1) integrating a privacy management system with DLP tools; (2) using the DLP tools to identify sensitive information that is stored in computer memory outside of the context of the privacy management system; and (3) in response to the sensitive data being discovered by the DLP tool, displaying each area of sensitive data to a privacy officer (e.g., similar to pending transactions in a checking account that have not been reconciled). A designated privacy officer may then select a particular entry and either match it up (e.g., reconcile it) with an existing data flow or campaign in the privacy management system, or trigger a new privacy assessment to be done on the data to capture the related privacy attributes and data flow information.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 17/316,179, filed May 10, 2021, which is a continuation-in-partof U.S. patent application Ser. No. 17/030,714, filed Sep. 24, 2020, nowU.S. Pat. No. 11,004,125, issued May 11, 2021, which is acontinuation-in-part of U.S. patent application Ser. No. 16/719,488,filed Dec. 18, 2019, now U.S. Pat. No. 10,853,859, issued Dec. 1, 2020,which is a continuation of U.S. patent application Ser. No. 16/578,712,filed Sep. 23, 2019, now U.S. Pat. No. 10,706,447, issued Jul. 7, 2020,which is a continuation-in-part of U.S. patent application Ser. No.16/237,083, filed Dec. 31, 2018, now U.S. Pat. No. 10,423,996, issuedSep. 24, 2019, which is a continuation-in-part of U.S. patentapplication Ser. No. 15/894,809, filed Feb. 12, 2018, now U.S. Pat. No.10,169,788, issued Jan. 1, 2019, which is a continuation of U.S. patentapplication Ser. No. 15/619,459, filed Jun. 10, 2017, now U.S. Pat. No.9,892,444, issued Feb. 13, 2018, which claims priority from U.S.Provisional Patent Application Ser. No. 62/360,123, filed Jul. 8, 2016;U.S. Provisional Patent Application Ser. No. 62/353,802, filed Jun. 23,2016; and U.S. Provisional Patent Application Ser. No. 62/348,695, filedJun. 10, 2016, and is also a continuation-in-part of U.S. patentapplication Ser. No. 15/256,419, filed Sep. 2, 2016, now U.S. Pat. No.9,691,090, issued Jun. 27, 2017, which is a continuation of U.S. patentapplication Ser. No. 15/169,643, filed May 31, 2016, now U.S. Pat. No.9,892,441, issued Feb. 13, 2018, which claims priority from U.S.Provisional Patent Application Ser. No. 62/317,457, filed Apr. 1, 2016.All of the above-referenced patents and patent applications are herebyincorporated by reference in their entirety.

INCORPORATION BY REFERENCE

This application hereby incorporates the disclosures of following patentapplications by reference in their entirety: U.S. patent applicationSer. No. 15/619,212, entitled “Data Processing Systems And Methods ForEfficiently Assessing The Risk Of Privacy Campaigns,” which was filedJun. 9, 2017, now U.S. Pat. No. 9,892,442, issued Feb. 13, 2018; U.S.patent application Ser. No. 15/619,237, entitled “Data Processing AndCommunication Systems And Methods For Operationalizing PrivacyCompliance And Regulation And Related Systems And Methods,” which wasfiled Jun. 9, 2017, now abandoned; U.S. patent application Ser. No.15/619,251, entitled “Data Processing Systems For Measuring PrivacyMaturity Within An Organization,” which was filed Jun. 9, 2017, now U.S.Pat. No. 10,032,172, issued Jul. 24, 2018; U.S. patent application Ser.No. 15/254,901, entitled “Data Processing Systems and Methods forPerforming Privacy Assessments and Monitoring of New Versions ofComputer Code for Privacy Compliance,” which was filed Sep. 1, 2016, nowU.S. Pat. No. 9,729,583, issued Aug. 8, 2017; U.S. patent applicationSer. No. 15/619,375, entitled “Data Processing Systems For GeneratingData Maps,” which was filed Jun. 9, 2017, now abandoned; U.S. patentapplication Ser. No. 15/619,382, entitled “Data Processing Systems ForModifying Privacy Campaign Data Via Electronic Messaging Systems,” whichwas filed Jun. 9, 2017, now U.S. Pat. No. 9,892,443, issued Feb. 13,2018; U.S. patent application Ser. No. 15/619,451, entitled “DataProcessing Systems and Methods For Operationalizing Privacy ComplianceVia Integrated Mobile Applications,” which was filed Jun. 10, 2017, nowU.S. Pat. No. 9,898,769, issued Feb. 20, 2018; U.S. patent applicationSer. No. 15/619,469, entitled “Data Processing Systems and Methods forGenerating Personal Data Inventories for Organizations and OtherEntities,” which was filed Jun. 10, 2017, now U.S. Pat. No. 10,026,110,issued Jul. 17, 2018; U.S. patent application Ser. No. 15/619,455,entitled “Data Processing Systems And Communications Systems And MethodsFor Integrating Privacy Compliance Systems With Software Development AndAgile Tools For Privacy Design,” which was filed Jun. 10, 2017, now U.S.Pat. No. 9,851,966, issued Dec. 26, 2017; U.S. patent application Ser.No. 15/619,278, entitled “Data Processing Systems For MonitoringModifications To User System Inputs To Predict Potential Inputs OfIncorrect Or Incomplete Data,” which was filed Jun. 9, 2017, nowabandoned; and U.S. patent application Ser. No. 15/619,459, entitled“Data Processing Systems And Communication Systems And Methods For TheEfficient Generation Of Privacy Risk Assessments,” which was filed Jun.10, 2017, now U.S. Pat. No. 9,892,444, issued Feb. 13, 2018.

TECHNICAL FIELD

This disclosure relates to a data processing system and methods forretrieving data regarding a plurality of privacy campaigns, and forusing that data to assess a relative risk associated with the dataprivacy campaign, provide an audit schedule for each campaign, andelectronically display campaign information.

BACKGROUND

Over the past years, privacy and security policies, and relatedoperations have become increasingly important. Breaches of data networkshandling personal data, leading to the unauthorized access of thepersonal data (which may include sensitive personal data) have becomemore frequent among companies and other organizations of all sizes. Suchpersonal data may include, but is not limited to, personallyidentifiable information (PII), which may be information that directly(or indirectly) identifies an individual or entity. Examples of PIIinclude names, addresses, dates of birth, social security numbers, andbiometric identifiers such as a person's fingerprints or picture. Otherpersonal data may include, for example, customers' Internet browsinghabits, purchase history, or even their preferences (i.e., likes anddislikes, as provided or obtained through social media). While not allpersonal data may be sensitive, in the wrong hands, this kind ofinformation may have a negative impact on the individuals or entitieswhose sensitive personal data is collected, including identity theft andembarrassment. Not only would this breach have the potential of exposingindividuals to malicious wrongdoing, the fallout from such breaches mayresult in damage to reputation, potential liability, and costly remedialaction for the organizations that collected the information and thatwere under an obligation to maintain its confidentiality and security.These breaches may result in not only financial loss, but loss ofcredibility, confidence, and trust from individuals, stakeholders, andthe public.

Many organizations that obtain, use, and transfer personal data,including sensitive personal data, have begun to implement data controlswithin their data networks to ensure they are handling personal withinthe data networks in a secure manner. However, a technical challengethat is often encountered in implementing such data controls isidentifying where in the data networks such controls should beimplemented. This is because often these data networks are comprised ofa significant number of components and/or processing activities that mayinvolve the personal data. As a result, an organization may havesignificant difficultly in identify the flow of the personal datathrough a data network and the various components and/or processingactivities involved in the data flow. This can further result into thecompany not recognizing and/or identifying the appropriate data controlsthat need to be implemented for the data network and the correspondingcomponents and processing activities in which the data controls shouldbe implemented. Therefore, a need exists in the art for improvedsystems, methods, and tools for identifying and representing data flowsof specific types of data (e.g., personal data) through a data network.

SUMMARY

A method, according to various aspects, comprises: (1) identifying, bycomputing hardware, a plurality of pieces of data associated with a datasubject in a data map; (2) determining, by the computing hardware, thatthe plurality of pieces of data comprise sensitive data; (3)determining, by the computing hardware, that a first portion of thesensitive data exactly matches privacy campaign data stored in a privacycampaign data record for a data processing activity; and (4)reconciling, by the computing hardware based on determining that thefirst portion of the sensitive data exactly matches the privacy campaigndata, the plurality of pieces of data with a data flow for the dataprocessing activity by: (A) determining whether each of the plurality ofpieces of data is represented in the data flow; (B) in response todetermining that at least one of the plurality of pieces of data is notrepresented in the data flow, updating the data flow by associating theat least one of the plurality of pieces of data with the data flow; and(C) defining, in the data flow, a privacy related attribute for the atleast one of the plurality of pieces of data, the privacy relatedattribute including an indication of the data subject. In some aspects,the method comprises facilitating, by the computing hardware using thedata flow, performance of network operations for retrieving dataresponsive to a query related to one or more data repositoriesidentified in the data flow, the query including a request to identifypersonal data associated with the data subject.

In some aspects, reconciling the plurality of pieces of data with thedata flow for the processing activity further comprises: (1) generatinga user interface comprising a respective interactive element for each ofthe plurality of pieces of data; (2) providing the user interface fordisplay on a computing device; and (3) receiving, via each respectiveinteractive element, an indication of an inclusion status of each of theplurality of pieces of data in the data flow. In other aspects,determining whether each of the plurality of pieces of data isrepresented in the data flow comprises determining whether each of theplurality of pieces of data is represented in the data flow based on theindication of the inclusion status. In particular aspects, the methodcomprises, in response to determining that at least one of the pluralityof pieces of data is not represented in the data flow, initiating a riskassessment for the data processing activity.

In some aspects, the method comprises generating, by the computinghardware, a graphical user interface that comprises a visualrepresentation of the data flow by: (1) configuring a first visualindication of a first data asset in the data flow, (2) configuring asecond visual indication of a second data asset in the data flow, (3)configuring a third visual indication of an exchange of the at least oneof the plurality of pieces of data between the first data asset and thesecond data asset based on the data flow. In some aspects, the methodcomprises providing, by the computing hardware, the graphical userinterface for display on a computing device. In particular aspects, themethod further comprises determining, by the computing hardware, anencryption status of the at least one of the plurality of pieces ofdata; and the third visual indication reflects the encryption status. Invarious aspects, the method comprises modifying, by the computinghardware, the encryption status of the at least one of the plurality ofpieces of data in response to determining that the at least one of theplurality of pieces of data is not represented in the data flow.

A system, in various aspects, comprises a non-transitorycomputer-readable medium storing instructions and a processing devicecommunicatively coupled to the non-transitory computer-readable medium.In some aspects, the processing device is configured to execute theinstructions and thereby perform operations comprising: (1) identifyinga plurality of pieces of data associated with a data subject in a datamap; (2) determining that the plurality of pieces of data comprisesensitive data; (3) determining that a first portion of the sensitivedata exactly matches privacy campaign data stored in a privacy campaigndata record for a data processing activity; and (4) reconciling, basedon determining that the first portion of the sensitive data exactlymatches the privacy campaign data, the plurality of pieces of data witha data flow for the data processing activity by: (A) determining whethereach of the plurality of pieces of data is represented in the data flow;(B) in response to determining that at least one of the plurality ofpieces of data is not represented in the data flow, updating the dataflow by associating the at least one of the plurality of pieces of datawith the data flow; and (C) defining, in the data flow, a privacyrelated attribute for the at least one of the plurality of pieces ofdata, the privacy related attribute including an indication of the datasubject.

In some aspects, the operations further comprise facilitating, using thedata flow, performance of network operations for retrieving dataresponsive to a query related to one or more data repositoriesidentified in the data flow, the query including a request to identifypersonal data associated with the data subject. In various otheraspects, reconciling the plurality of pieces of data with the data flowfor the processing activity further comprises: (1) generating a userinterface comprising a respective interactive element for each of theplurality of pieces of data; (2) providing the user interface fordisplay on a computing device; and (3) receiving, via each respectiveinteractive element, an indication of an inclusion status of each of theplurality of pieces of data in the data flow. In such aspects,determining whether each of the plurality of pieces of data isrepresented in the data flow comprises determining whether each of theplurality of pieces of data is represented in the data flow based on theindication of the inclusion status.

In various aspects, the operations further comprise, in response todetermining that at least one of the plurality of pieces of data is notrepresented in the data flow, initiating a risk assessment for the dataprocessing activity. In other aspects, the operations further comprisedefining at least a second privacy related attribute for the at leastone of the plurality of pieces of data based on data responsive to therisk assessment for the data processing activity. In particular aspects,the operations comprise generating a graphical user interface thatcomprises a visual representation of the data flow by: (1) configuring afirst visual indication of a first data asset in the data flow, (2)configuring a second visual indication of a second data asset in thedata flow, (3) configuring a third visual indication of an exchange ofthe at least one of the plurality of pieces of data between the firstdata asset and the second data asset based on the data flow; and (4)providing the graphical user interface for display on a computingdevice.

In some aspects, the operations further comprise determining anencryption status of the at least one of the plurality of pieces ofdata, and the third visual indication reflects the encryption status. Instill other aspects, the operations further comprise modifying theencryption status of the at least one of the plurality of pieces of datain response to determining that the at least one of the plurality ofpieces of data is not represented in the data flow.

In various aspects, a non-transitory computer-readable medium havingprogram code that is stored thereon. In some aspects, the program codeis executable by one or more processing devices for performingoperations comprising: (1) identifying a plurality of pieces of dataassociated with a data subject in a data map; (2) determining that theplurality of pieces of data comprise sensitive data; (3) determiningthat a first portion of the sensitive data exactly matches privacycampaign data stored in a privacy campaign data record for a dataprocessing activity; and (4) reconciling, based on determining that thefirst portion of the sensitive data exactly matches the privacy campaigndata, the plurality of pieces of data with a data flow for the dataprocessing activity by: (1) determining whether each of the plurality ofpieces of data is represented in the data flow; (2) in response todetermining that at least one of the plurality of pieces of data is notrepresented in the data flow, updating the data flow by associating theat least one of the plurality of pieces of data with the data flow; and(3) defining, in the data flow, a privacy related attribute for the atleast one of the plurality of pieces of data, the privacy relatedattribute including an indication of the data subject. In variousaspects, reconciling the plurality of pieces of data with the data flowfor the processing activity further comprises: (1) generating a userinterface comprising a respective interactive element for each of theplurality of pieces of data; (2) providing the user interface fordisplay on a computing device; and (3) receiving, via each respectiveinteractive element, an indication of an inclusion status of each of theplurality of pieces of data in the data flow. In some aspects,determining whether each of the plurality of pieces of data isrepresented in the data flow comprises determining whether each of theplurality of pieces of data is represented in the data flow based on theindication of the inclusion status.

In some aspects, the operations further comprise, in response todetermining that at least one of the plurality of pieces of data is notrepresented in the data flow, initiating a risk assessment for the dataprocessing activity. In other aspects, the operations further comprisedefining at least a second privacy related attribute for the at leastone of the plurality of pieces of data based on data responsive to therisk assessment for the data processing activity. In particular aspects,the operations further comprise generating a graphical user interfacethat comprises a visual representation of the data flow by: (1)configuring a first visual indication of a first data asset in the dataflow, (2) configuring a second visual indication of a second data assetin the data flow, (3) configuring a third visual indication of anexchange of the at least one of the plurality of pieces of data betweenthe first data asset and the second data asset based on the data flow;and (4) providing the graphical user interface for display on acomputing device.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of a system and method for operationalizing privacycompliance and assessing risk of privacy campaigns are described below.In the course of this description, reference will be made to theaccompanying drawings, which are not necessarily drawn to scale, andwherein:

FIG. 1 is diagram illustrating an exemplary network environment in whichthe present systems and methods for operationalizing privacy compliancemay operate.

FIG. 2 is a schematic diagram of a computer (such as the server 120, oruser device 140, 150, 160, 170, 180, 190) that is suitable for use invarious embodiments.

FIG. 3 is a diagram illustrating an example of the elements (e.g.,subjects, owner, etc.) that may be involved in privacy compliance.

FIG. 4 is a flow chart showing an example of a process performed by theMain Privacy Compliance Module.

FIG. 5 is a flow chart showing an example of a process performed by theRisk Assessment Module.

FIG. 6 is a flow chart showing an example of a process performed by thePrivacy Audit Module.

FIG. 7 is a flow chart showing an example of a process performed by theData Flow Diagram Module.

FIG. 8 is an example of a graphical user interface (GUI) showing adialog that allows for the entry of description information related to aprivacy campaign.

FIG. 9 shows example of a notification generated by the system that mayinform to a business representative (e.g., owner) that they have beenassigned to a particular campaign.

FIG. 10 is an example of a GUI showing a dialog allowing entry of thetype of personal data that is being collected for a campaign.

FIG. 11 is an example of a GUI that shows a dialog that allowscollection of campaign data regarding the subject from which thepersonal data was collected.

FIG. 12 is an example of a GUI that shows a dialog for inputtinginformation regarding where the personal data related to a campaign isstored.

FIG. 13 is an example of a GUI that shows information regarding theaccess of the personal data related to a campaign.

FIG. 14 is an example of an instant messaging session overlaid on top ofa GUI, wherein the GUI contains prompts for the entry or selection ofcampaign data.

FIG. 15 is an example of a GUI showing an inventory page.

FIG. 16 is an example of a GUI showing campaign data, including a dataflow diagram.

FIG. 17 is an example of a GUI showing a web page that allows editing ofcampaign data.

FIGS. 18A and 18B depict a flow chart showing an example of a processperformed by the Data Privacy Compliance Module.

FIGS. 19A and 19B depict a flow chart showing an example of a processperformed by the Privacy Assessment Reporting Module.

DETAILED DESCRIPTION

Various embodiments now will be described more fully hereinafter withreference to the accompanying drawings. It should be understood that theinvention may be embodied in many different forms and should not beconstrued as limited to the embodiments set forth herein. Rather, theseembodiments are provided so that this disclosure will be thorough andcomplete, and will fully convey the scope of the invention to thoseskilled in the art. Like numbers refer to like elements throughout.

Overview and Technical Contributions of Various Aspects

As previously noted, a technical challenge often encountered by manyentities (e.g., organizations) that handle specific types of data (e.g.,such as personal data, sensitive data, etc.) is identifying variousflows of the data through a data network. A data network may be used byan entity in performing different tasks involving specific data such ascollecting, storing, transferring, processing, and/or the like of thedata. The term “handling” is used herein with respect to an entity (dataassets and/or data processing activities thereof) performing differenttasks involving the specific data. The data network may include variousdata assets and data processing activities. A data asset may include anycomponent that may be involved in handling specific data for the entity.For example, a data asset may include a software application, “internetof things” computerized device, computing hardware, database, website,data-center, server, and or the like. A data processing activity mayinclude an enterprise or action preformed in processing data for theentity. For example, a data processing activity may involve thecollecting and storing of credit card data from individuals through awebform provided on a website.

Thus, a multitude of data processing activities representing variousdata flows may be involved in handling specific data through a datanetwork for an entity. Further, the data flows may comprise a multitudeof data assets that are involved in handling the specific data withinthe data flows. Therefore, a single data processing activity may utilizemultiple data assets, in various combinations, in processing thespecific data through the data network. That is to say, any one dataprocessing activity may represent a data flow involving the specificdata that utilizes multiple data assets, and any one data asset can beutilized in multiple data processing activities representing multipledata flows. This can provide to be a significant technical challenge forthe entity in identifying the flow of the specific data through the datanetwork due to the numerous combinations of data assets and/or dataprocessing activities that may overlap across various data flows. Thetechnical challenge can be even more daunting as the number of dataassets and/or data processing activities increases for the data network,as well as the volume of the specific data handled by the data network.

An important reason for identifying data flows involving specific datathrough a data network is because such data may require the network toimplement data controls for handling the specific data within the datanetwork. Therefore, identifying the data flows for specific data (e.g.,a specific type of data) within a data network, as well as identifyingthe data assets and data processing activities involved in the dataflows, becomes very important in ensuring that the appropriate/requireddata controls are implemented for the data assets and data processingactivities. For example, it may be necessary to ensure that eachparticular data asset through which a particular piece of data flows aspart of a processing activity satisfies required data handling controls.

For example, a specific type of data that requires data controls to beimplemented in handling the data is personal data of individuals (datasubjects). Various privacy regulations, laws, and the like define datacontrols that must be implemented by an entity in handling the personaldata of data subjects. A primary reason for these controls is to ensurean entity is handling the personal data in a manner that minimizes therisk of the personal data being exposed to unauthorized parties. Forexample, such privacy regulations, laws, and the like may require datacontrols such as implementing encryption of the personal data for datatransfers, implementing access controls on storage devices used forstoring the personal data, anatomizing the personal data beforedisplaying the data via a graphical user interface, and/or the like.Many of these data controls are required to be implemented with respectto various data assets and data processing activities that are involvedin handling the personal data. Therefore, identifying the data assetsand/or data processing activities that are involved in handling thepersonal data by an entity within a data network is critical in ensuringthe proper data controls for the data assets and data processingactivities are in place.

Accordingly, various embodiments of the disclosure address the technicalchallenges discussed herein by providing a method of reconcilingsensitive data with an existing data flow by determining other dataassociated with the sensitive data is represented in the data flow. Inparticular, the method involves matching identified data to existingsensitive data in a data flow, and then adding the identified sensitivedata that is not in the data flow to the data flow. In this way, themethod involves maintaining an up-to-date, accurate representation ofthe flow of data as part of the processing activity, that maintainsprivacy-related attributes for the data involved in the data flow. Thesystem can then identify, for each piece of sensitive data, exactlywhere in the system that the data travels and from where, to ensure thatthe data is handled properly at every point in the flow.

Additionally, many organizations have attempted to implement operationalprocesses that comply with certain rights related to a data subject'spersonal data that is collected, stored, or otherwise processed by anorganization. These rights may include, for example, a right to obtainconfirmation of whether a particular organization is processing theirpersonal data, a right to obtain information about the purpose of theprocessing (e.g., one or more reasons for which the personal data wascollected), and other such rights. Some regulations requireorganizations to comply with requests for such information (e.g., DataSubject Access Requests) within relatively short periods of time (e.g.,30 days).

However, a technical challenge often encountered by many organizationsin their processing of personal data while complying with a datasubject's rights related to their personal data that is collected,stored, or otherwise processed by an organization is facilitating (e.g.,allowing) the data subject's exercise of such rights when the personaldata involved may exist over multiple data sources (e.g., computingdevices, data storage, and/or the like) found within multiple datastorage systems. As a result, an organization's processing of requestsreceived from data subjects (e.g., individuals) who are exercising theirrights related to their personal data can require a significant amountof computing resources. Accordingly, various aspects of the presentdisclosure also address the technical challenges discussed herein, byidentifying a flow of personal data across different systems operated bya particular entity, in order to maintain an updated map of personaldata that can be used to identify such data when serving such requests.

According to exemplary embodiments, a system for operationalizingprivacy compliance is described herein. The system may be comprised ofone or more servers and client computing devices that execute softwaremodules that facilitate various functions.

A Main Privacy Compliance Module is operable to allow a user to initiatethe creation of a privacy campaign (i.e., a business function, system,product, technology, process, project, engagement, initiative, campaign,etc., that may utilize personal data collected from one or more personsor entities). The personal data may contain PII that may be sensitivepersonal data. The user can input information such as the name anddescription of the campaign. The user may also select whether he/shewill take ownership of the campaign (i.e., be responsible for providingthe information needed to create the campaign and oversee the conductingof privacy audits related to the campaign), or assign the campaign toone or more other persons. The Main Privacy Compliance Module cangenerate a sequence or serious of GUI windows that facilitate the entryof campaign data representative of attributes related to the privacycampaign (e.g., attributes that might relate to the description of thepersonal data, what personal data is collected, whom the data iscollected from, the storage of the data, and access to that data).

Based on the information input, a Risk Assessment Module may be operableto take into account Weighting Factors and Relative Risk Ratingsassociated with the campaign in order to calculate a numerical RiskLevel associated with the campaign, as well as an Overall RiskAssessment for the campaign (i.e., low-risk, medium risk, or high risk).The Risk Level may be indicative of the likelihood of a breach involvingpersonal data related to the campaign being compromised (i.e., lost,stolen, accessed without authorization, inadvertently disclosed,maliciously disclosed, etc.). An inventory page can visually depict theRisk Level for one or more privacy campaigns.

After the Risk Assessment Module has determined a Risk Level for acampaign, a Privacy Audit Module may be operable to use the Risk Levelto determine an audit schedule for the campaign. The audit schedule maybe editable, and the Privacy Audit Module also facilitates the privacyaudit process by sending alerts when a privacy audit is impending, orsending alerts when a privacy audit is overdue.

The system may also include a Data Flow Diagram Module for generating adata flow diagram associated with a campaign. An exemplary data flowdiagram displays one or more shapes representing the source from whichdata associated with the campaign is derived, the destination (orlocation) of that data, and which departments or software systems mayhave access to the data. The Data Flow Diagram Module may also generateone or more security indicators for display. The indicators may include,for example, an “eye” icon to indicate that the data is confidential, a“lock” icon to indicate that the data, and/or a particular flow of data,is encrypted, or an “unlocked lock” icon to indicate that the data,and/or a particular flow of data, is not encrypted. Data flow lines maybe colored differently to indicate whether the data flow is encrypted orunencrypted.

The system also provides for a Communications Module that facilitatesthe creation and transmission of notifications and alerts (e.g., viaemail). The Communications Module may also instantiate an instantmessaging session and overlay the instant messaging session over one ormore portions of a GUI in which a user is presented with prompts toenter or select information.

Technical Contributions of Various Embodiments

An entity that handles (e.g., collects, receives, transmits, stores,processes, shares, and/or the like) sensitive and/or personalinformation associated with particular individuals (e.g., personallyidentifiable information (PII) data, sensitive data, personal data,etc.) may be subject to various laws, regulations, and/or requirementsregarding the handling of such personal data. These laws, regulations,and/or requirements may vary based on the jurisdiction in which theentity is operating, the jurisdiction in which a person or entityassociated with the data (“data subject”) handled by the entity islocated, and/or the jurisdiction in which the data is handled. Overtime, the entity may integrate one or more systems with one or moreother systems. The resulting integrated systems may be subject to one ormore such laws, regulations, and/or requirements. Therefore, the entitymay need to ensure that it handles the data processed across suchintegrated systems in compliance with the applicable laws, regulations,and/or requirements.

In various embodiments, a subsystem within an integrated system maycontain one or more pieces of data that may be the same as one or morepieces of data stored by another subsystem. However, each such subsystemmay identify or classify the same one or more pieces of data in adifferent manner. Moreover, one such subsystem may contain dataassociated with the one or more pieces of data that is not stored on theother subsystem containing the same one or more pieces of data, eventhough it may be desirable to do so.

Accordingly, various embodiments of present disclosure overcome many ofthe technical challenges associated with determining whether data isconsistent across interoperating systems and, if not, reconciling dataacross such systems. Specifically, various embodiments of the disclosureare directed to a computational framework configured for determiningwhether pieces of data on a first system correspond to (e.g., match) oneor more pieces of data on another system. If they do, in variousembodiments, the system may determine whether all corresponding data ispresent on both systems and, if not, take actions to associate allcorresponding data with both systems. For example, the system mayautomatically determine whether a piece of sensitive data on a firstsystem is the same as a piece of data on a second system, and, if it is,copy the data on the first system that is associated with the sensitivedata to a data structure (e.g., a data flow) stored on the secondsystem. In various embodiments, the system may also, or instead,initiate a process to generate a new data structure (e.g., a data flow)on the second system and associate the sensitive data and associateddata with the new data structure. The various embodiments automate adata reconciliation process that, if performed manually by a user, wouldbe cumbersome and time consuming.

Accordingly, various embodiments of the disclosure provided herein aremore effective, efficient, timely, accurate, and faster in reconcilingdata across two or more interoperable systems. In addition, variousembodiments provided herein can facilitate the identification ofsensitive data processed by an entity and/or one or more associatedprivacy campaigns and the reconciliation of such data to ensureconsistency across systems and assist in compliance with one or moreapplicable regulations and/or requirements. By properly identifying dataprocessed across various interoperable systems, the various embodimentshelp ensure that such data is handled according to one or moreapplicable requirements and regulations. This is especially advantageouswhen one or more systems operating within an integrated system is notconfigured for a privacy management environment but is interoperatingwith privacy management systems. In facilitating the interoperation ofsuch systems, the various embodiments of the present disclosure makemajor technical contributions to improving the computational efficiencyand reliability of various privacy management systems and procedures forensuring compliance with one or more particular regulations and/orrequirements associated with privacy management. This in turn translatesto more computationally efficient software systems. Further detail isnow provided for different aspects of various embodiments of thedisclosure.

Exemplary Technical Platforms

As will be appreciated by one skilled in the relevant field, a systemfor operationalizing privacy compliance and assessing risk of privacycampaigns may be, for example, embodied as a computer system, a method,or a computer program product. Accordingly, various embodiments may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, or an embodiment combining software and hardware aspects.Furthermore, particular embodiments may take the form of a computerprogram product stored on a computer-readable storage medium havingcomputer-readable instructions (e.g., software) embodied in the storagemedium. Various embodiments may take the form of web, mobile, wearablecomputer-implemented, computer software. Any suitable computer-readablestorage medium may be utilized including, for example, hard disks,compact disks, DVDs, optical storage devices, and/or magnetic storagedevices.

Various embodiments are described below with reference to block diagramsand flowchart illustrations of methods, apparatuses (e.g., systems) andcomputer program products. It should be understood that each step of theblock diagrams and flowchart illustrations, and combinations of steps inthe block diagrams and flowchart illustrations, respectively, may beimplemented by a computer executing computer program instructions. Thesecomputer program instructions may be loaded onto a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructionswhich execute on the computer or other programmable data processingapparatus to create means for implementing the functions specified inthe flowchart step or steps

These computer program instructions may also be stored in acomputer-readable memory that may direct a computer or otherprogrammable data processing apparatus to function in a particularmanner such that the instructions stored in the computer-readable memoryproduce an article of manufacture that is configured for implementingthe function specified in the flowchart step or steps. The computerprogram instructions may also be loaded onto a computer or otherprogrammable data processing apparatus to cause a series of operationalsteps to be performed on the computer or other programmable apparatus toproduce a computer implemented process such that the instructions thatexecute on the computer or other programmable apparatus provide stepsfor implementing the functions specified in the flowchart step or steps.

Accordingly, steps of the block diagrams and flowchart illustrationssupport combinations of mechanisms for performing the specifiedfunctions, combinations of steps for performing the specified functions,and program instructions for performing the specified functions. Itshould also be understood that each step of the block diagrams andflowchart illustrations, and combinations of steps in the block diagramsand flowchart illustrations, may be implemented by special purposehardware-based computer systems that perform the specified functions orsteps, or combinations of special purpose hardware and other hardwareexecuting appropriate computer instructions.

Example System Architecture

FIG. 1 is a block diagram of a System 100 according to a particularembodiment. As may be understood from this figure, the System 100includes one or more computer networks 110, a Server 120, a StorageDevice 130 (which may contain one or more databases of information), oneor more remote client computing devices such as a tablet computer 140, adesktop or laptop computer 150, or a handheld computing device 160, suchas a cellular phone, browser and Internet capable set-top boxes 170connected with a TV 180, or even smart TVs 180 having browser andInternet capability. The client computing devices attached to thenetwork may also include copiers/printers 190 having hard drives (asecurity risk since copies/prints may be stored on these hard drives).The Server 120, client computing devices, and Storage Device 130 may bephysically located in a central location, such as the headquarters ofthe organization, for example, or in separate facilities. The devicesmay be owned or maintained by employees, contractors, or other thirdparties (e.g., a cloud service provider). In particular embodiments, theone or more computer networks 115 facilitate communication between theServer 120, one or more client computing devices 140, 150, 160, 170,180, 190, and Storage Device 130.

The one or more computer networks 115 may include any of a variety oftypes of wired or wireless computer networks such as the Internet, aprivate intranet, a public switched telephone network (PSTN), or anyother type of network. The communication link between the Server 120,one or more client computing devices 140, 150, 160, 170, 180, 190, andStorage Device 130 may be, for example, implemented via a Local AreaNetwork (LAN) or via the Internet.

Example Computer Architecture Used within the System

FIG. 2 illustrates a diagrammatic representation of the architecture ofa computer 200 that may be used within the System 100, for example, as aclient computer (e.g., one of computing devices 140, 150, 160, 170, 180,190, shown in FIG. 1), or as a server computer (e.g., Server 120 shownin FIG. 1). In exemplary embodiments, the computer 200 may be suitablefor use as a computer within the context of the System 100 that isconfigured to operationalize privacy compliance and assess risk ofprivacy campaigns. In particular embodiments, the computer 200 may beconnected (e.g., networked) to other computers in a LAN, an intranet, anextranet, and/or the Internet. As noted above, the computer 200 mayoperate in the capacity of a server or a client computer in aclient-server network environment, or as a peer computer in apeer-to-peer (or distributed) network environment. The computer 200 maybe a personal computer (PC), a tablet PC, a set-top box (STB), aPersonal Digital Assistant (PDA), a cellular telephone, a web appliance,a server, a network router, a switch or bridge, or any other computercapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that computer. Further, while only asingle computer is illustrated, the term “computer” shall also be takento include any collection of computers that individually or jointlyexecute a set (or multiple sets) of instructions to perform any one ormore of the methodologies discussed herein.

An exemplary computer 200 includes a processing device 202, a mainmemory 204 (e.g., read-only memory (ROM), flash memory, dynamic randomaccess memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM(RDRAM), etc.), a static memory 206 (e.g., flash memory, static randomaccess memory (SRAM), etc.), and a data storage device 218, whichcommunicate with each other via a bus 232.

The processing device 202 represents one or more general-purposeprocessing devices such as a microprocessor, a central processing unit,or the like. More particularly, the processing device 202 may be acomplex instruction set computing (CISC) microprocessor, reducedinstruction set computing (RISC) microprocessor, very long instructionword (VLIW) microprocessor, or processor implementing other instructionsets, or processors implementing a combination of instruction sets. Theprocessing device 202 may also be one or more special-purpose processingdevices such as an application specific integrated circuit (ASIC), afield programmable gate array (FPGA), a digital signal processor (DSP),network processor, or the like. The processing device 202 may beconfigured to execute processing logic 226 for performing variousoperations and steps discussed herein.

The computer 200 may further include a network interface device 208. Thecomputer 200 also may include a video display unit 210 (e.g., a liquidcrystal display (LCD) or a cathode ray tube (CRT)), an alphanumericinput device 212 (e.g., a keyboard), a cursor control device 214 (e.g.,a mouse), and a signal generation device 216 (e.g., a speaker). The datastorage device 218 may include a non-transitory computer-readablestorage medium 230 (also known as a non-transitory computer-readablestorage medium or a non-transitory computer-readable medium) on which isstored one or more sets of instructions 222 (e.g., software, softwaremodules) embodying any one or more of the methodologies or functionsdescribed herein. The software 222 may also reside, completely or atleast partially, within main memory 204 and/or within processing device202 during execution thereof by computer 200—main memory 204 andprocessing device 202 also constituting computer-accessible storagemedia. The software 222 may further be transmitted or received over anetwork 220 via network interface device 208.

While the computer-readable storage medium 230 is shown in an exemplaryembodiment to be a single medium, the terms “computer-readable storagemedium” and “machine-accessible storage medium” should be understood toinclude a single medium or multiple media (e.g., a centralized ordistributed database, and/or associated caches and servers) that storethe one or more sets of instructions. The term “computer-readablestorage medium” should also be understood to include any medium that iscapable of storing, encoding or carrying a set of instructions forexecution by the computer and that cause the computer to perform any oneor more of the methodologies of the present invention. The term“computer-readable storage medium” should accordingly be understood toinclude, but not be limited to, solid-state memories, optical andmagnetic media, etc.

Exemplary System Platform

According to various embodiments, the processes and logic flowsdescribed in this specification may be performed by a system (e.g.,System 100) that includes, but is not limited to, one or moreprogrammable processors (e.g., processor 202) executing one or morecomputer program modules to perform functions by operating on input dataand generating output, thereby tying the process to a particular machine(e.g., a machine programmed to perform the processes described herein).This includes processors located in one or more of client computers(e.g., client computers 140, 150, 160, 170, 180, 190 of FIG. 1). Thesedevices connected to network 110 may access and execute one or moreInternet browser-based program modules that are “served up” through thenetwork 110 by one or more servers (e.g., server 120 of FIG. 1), and thedata associated with the program may be stored on a one or more storagedevices, which may reside within a server or computing device (e.g.,Main Memory 204, Static Memory 206), be attached as a peripheral storagedevice to the one or more servers or computing devices, or attached tothe network (e.g., Storage 130).

The System 100 facilitates the acquisition, storage, maintenance, use,and retention of campaign data associated with a plurality of privacycampaigns within an organization. In doing so, various aspects of theSystem 100 initiates and creates a plurality of individual data privacycampaign records that are associated with a variety of privacy-relatedattributes and assessment related meta-data for each campaign. Thesedata elements may include: the subjects of the sensitive information,the respective person or entity responsible for each campaign (e.g., thecampaign's “owner”), the location where the personal data will bestored, the entity or entities that will access the data, the parametersaccording to which the personal data will be used and retained, the RiskLevel associated with a particular campaign (as well as assessments fromwhich the Risk Level is calculated), an audit schedule, and otherattributes and meta-data. The System 100 may also be adapted tofacilitate the setup and auditing of each privacy campaign. Thesemodules may include, for example, a Main Privacy Compliance Module, aRisk Assessment Module, a Privacy Audit Module, a Data Flow DiagramModule, and a Communications Module (examples of which are describedbelow). It is to be understood that these are examples of modules ofvarious embodiments, but the functionalities performed by each module asdescribed may be performed by more (or less) modules. Further, thefunctionalities described as being performed by one module may beperformed by one or more other modules.

A. Example Elements Related to Privacy Campaigns

FIG. 3 provides a high-level visual overview of example “subjects” forparticular data privacy campaigns, exemplary campaign “owners,” variouselements related to the storage and access of personal data, andelements related to the use and retention of the personal data. Each ofthese elements may, in various embodiments, be accounted for by theSystem 100 as it facilitates the implementation of an organization'sprivacy compliance policy.

As may be understood from FIG. 3, sensitive information may be collectedby an organization from one or more subjects 300. Subjects may includecustomers whose information has been obtained by the organization. Forexample, if the organization is selling goods to a customer, theorganization may have been provided with a customer's credit card orbanking information (e.g., account number, bank routing number), socialsecurity number, or other sensitive information.

An organization may also possess personal data originating from one ormore of its business partners. Examples of business partners are vendorsthat may be data controllers or data processors (which have differentlegal obligations under EU data protection laws). Vendors may supply acomponent or raw material to the organization, or an outside contractorresponsible for the marketing or legal work of the organization. Thepersonal data acquired from the partner may be that of the partners, oreven that of other entities collected by the partners. For example, amarketing agency may collect personal data on behalf of theorganization, and transfer that information to the organization.Moreover, the organization may share personal data with one of itspartners. For example, the organization may provide a marketing agencywith the personal data of its customers so that it may conduct furtherresearch.

Other subjects 300 include the organization's own employees.Organizations with employees often collect personal data from theiremployees, including address and social security information, usuallyfor payroll purposes, or even prior to employment, for conducting creditchecks. The subjects 300 may also include minors. It is noted thatvarious corporate privacy policies or privacy laws may require thatorganizations take additional steps to protect the sensitive privacy ofminors.

Still referring to FIG. 3, within an organization, a particularindividual (or groups of individuals) may be designated to be an “owner”of a particular campaign to obtain and manage personal data. Theseowners 310 may have any suitable role within the organization. Invarious embodiments, an owner of a particular campaign will have primaryresponsibility for the campaign, and will serve as a resident expertregarding the personal data obtained through the campaign, and the waythat the data is obtained, stored, and accessed. As shown in FIG. 3, anowner may be a member of any suitable department, including theorganization's marketing, HR, R&D, or IT department. As will bedescribed below, in exemplary embodiments, the owner can always bechanged, and owners can sub-assign other owners (and othercollaborators) to individual sections of campaign data input andoperations.

Referring still to FIG. 3, the system may be configured to account forthe use and retention 315 of personal data obtained in each particularcampaign. The use and retention of personal data may include how thedata is analyzed and used within the organization's operations, whetherthe data is backed up, and which parties within the organization aresupporting the campaign.

The system may also be configured to help manage the storage and access320 of personal data. As shown in FIG. 3, a variety of different partiesmay access the data, and the data may be stored in any of a variety ofdifferent locations, including on-site, or in “the cloud”, i.e., onremote servers that are accessed via the Internet or other suitablenetwork.

B. Main Compliance Module

FIG. 4 illustrates an exemplary process for operationalizing privacycompliance. Main Privacy Compliance Module 400, which may be executed byone or more computing devices of System 100, may perform this process.In exemplary embodiments, a server (e.g., server 140) in conjunctionwith a client computing device having a browser, execute the MainPrivacy Compliance Module (e.g., computing devices 140, 150, 160, 170,180, 190) through a network (network 110). In various exemplaryembodiments, the Main Privacy Compliance Module 400 may call upon othermodules to perform certain functions. In exemplary embodiments, thesoftware may also be organized as a single module to perform variouscomputer executable routines.

I. Adding a Campaign

The process 400 may begin at step 405, wherein the Main PrivacyCompliance Module 400 of the System 100 receives a command to add aprivacy campaign. In exemplary embodiments, the user selects anon-screen button (e.g., the Add Data Flow button 1555 of FIG. 15) thatthe Main Privacy Compliance Module 400 displays on a landing page, whichmay be displayed in a graphical user interface (GUI), such as a window,dialog box, or the like. The landing page may be, for example, theinventory page 1500 below. The inventory page 1500 may display a list ofone or more privacy campaigns that have already been input into theSystem 100. As mentioned above, a privacy campaign may represent, forexample, a business operation that the organization is engaged in, orsome business record, that may require the use of personal data, whichmay include the personal data of a customer or some other entity.Examples of campaigns might include, for example, Internet UsageHistory, Customer Payment Information, Call History Log, CellularRoaming Records, etc. For the campaign “Internet Usage History,” amarketing department may need customers' on-line browsing patterns torun analytics. This might entail retrieving and storing customers' IPaddresses, MAC address, URL history, subscriber ID, and otherinformation that may be considered personal data (and even sensitivepersonal data). As will be described herein, the System 100, through theuse of one or more modules, including the Main Privacy Campaign Module400, creates a record for each campaign. Data elements of campaign datamay be associated with each campaign record that represents attributessuch as: the type of personal data associated with the campaign; thesubjects having access to the personal data; the person or personswithin the company that take ownership (e.g., business owner) forensuring privacy compliance for the personal data associated with eachcampaign; the location of the personal data; the entities having accessto the data; the various computer systems and software applications thatuse the personal data; and the Risk Level (see below) associated withthe campaign.

II. Entry of Privacy Campaign Related Information, Including Owner

At step 410, in response to the receipt of the user's command to add aprivacy campaign record, the Main Privacy Compliance Module 400initiates a routine to create an electronic record for a privacycampaign, and a routine for the entry data inputs of information relatedto the privacy campaign. The Main Privacy Compliance Module 400 maygenerate one or more graphical user interfaces (e.g., windows, dialogpages, etc.), which may be presented one GUI at a time. Each GUI mayshow prompts, editable entry fields, check boxes, radial selectors,etc., where a user may enter or select privacy campaign data. Inexemplary embodiments, the Main Privacy Compliance Module 400 displayson the graphical user interface a prompt to create an electronic recordfor the privacy campaign. A user may choose to add a campaign, in whichcase the Main Privacy Compliance Module 400 receives a command to createthe electronic record for the privacy campaign, and in response to thecommand, creates a record for the campaign and digitally stores therecord for the campaign. The record for the campaign may be stored in,for example, storage 130, or a storage device associated with the MainPrivacy Compliance Module (e.g., a hard drive residing on Server 110, ora peripheral hard drive attached to Server 110).

The user may be a person who works in the Chief Privacy Officer'sorganization (e.g., a privacy office rep, or privacy officer). Theprivacy officer may be the user that creates the campaign record, andenters initial portions of campaign data (e.g., “high level” datarelated to the campaign), for example, a name for the privacy campaign,a description of the campaign, and a business group responsible foradministering the privacy operations related to that campaign (forexample, though the GUI shown in FIG. 6). The Main Privacy ComplianceModule 400 may also prompt the user to enter a person or entityresponsible for each campaign (e.g., the campaign's “owner”). The ownermay be tasked with the responsibility for ensuring or attempting toensure that the privacy policies or privacy laws associated withpersonal data related to a particular privacy campaign are beingcomplied with. In exemplary embodiments, the default owner of thecampaign may be the person who initiated the creation of the privacycampaign. That owner may be a person who works in the Chief PrivacyOfficer's organization (e.g., a privacy office rep, or privacy officer).The initial owner of the campaign may designate someone else to be theowner of the campaign. The designee may be, for example, arepresentative of some business unit within the organization (a businessrep). Additionally, more than one owner may be assigned. For example,the user may assign a primary business rep, and may also assign aprivacy office rep as owners of the campaign.

In many instances, some or most of the required information related tothe privacy campaign record might not be within the knowledge of thedefault owner (i.e., the privacy office rep). The Main Data ComplianceModule 400 can be operable to allow the creator of the campaign record(e.g., a privacy officer rep) to designate one or more othercollaborators to provide at least one of the data inputs for thecampaign data. Different collaborators, which may include the one ormore owners, may be assigned to different questions, or to specificquestions within the context of the privacy campaign. Additionally,different collaborators may be designated to respond to pats ofquestions. Thus, portions of campaign data may be assigned to differentindividuals.

Still referring to FIG. 4, if at step 415 the Main Privacy ComplianceModule 400 has received an input from a user to designate a new ownerfor the privacy campaign that was created, then at step 420, the MainPrivacy Compliance Module 400 may notify that individual via a suitablenotification that the privacy campaign has been assigned to him or her.Prior to notification, the Main Privacy Compliance Module 400 maydisplay a field that allows the creator of the campaign to add apersonalized message to the newly assigned owner of the campaign to beincluded with that notification. In exemplary embodiments, thenotification may be in the form of an email message. The email mayinclude the personalized message from the assignor, a standard messagethat the campaign has been assigned to him/her, the deadline forcompleting the campaign entry, and instructions to log in to the systemto complete the privacy campaign entry (along with a hyperlink thattakes the user to a GUI providing access to the Main Privacy ComplianceModule 400. Also included may be an option to reply to the email if anassigned owner has any questions, or a button that when clicked on,opens up a chat window (i.e., instant messenger window) to allow thenewly assigned owner and the assignor a GUI in which they are able tocommunicate in real-time. An example of such a notification appears inFIG. 16 below. In addition to owners, collaborators that are assigned toinput portions of campaign data may also be notified through similarprocesses. In exemplary embodiments, The Main Privacy Compliance Module400 may, for example through a Communications Module, be operable tosend collaborators emails regarding their assignment of one or moreportions of inputs to campaign data. Or through the CommunicationsModule, selecting the commentators button brings up one or morecollaborators that are on-line (with the off-line users still able tosee the messages when they are back on-line. Alerts indicate that one ormore emails or instant messages await a collaborator.

At step 425, regardless of whether the owner is the user (i.e., thecreator of the campaign), “someone else” assigned by the user, or othercollaborators that may be designated with the task of providing one ormore items of campaign data, the Main Privacy Campaign Module 400 may beoperable to electronically receive campaign data inputs from one or moreusers related to the personal data related to a privacy campaign througha series of displayed computer-generated graphical user interfacesdisplaying a plurality of prompts for the data inputs. In exemplaryembodiments, through a step-by-step process, the Main Privacy CampaignModule may receive from one or more users' data inputs that includecampaign data like: (1) a description of the campaign; (2) one or moretypes of personal data to be collected and stored as part of thecampaign; (3) individuals from which the personal data is to becollected; (4) the storage location of the personal data, and (5)information regarding who will have access to the personal data. Theseinputs may be obtained, for example, through the graphical userinterfaces shown in FIGS. 8 through 13, wherein the Main ComplianceModule 400 presents on sequentially appearing GUIs the prompts for theentry of each of the enumerated campaign data above. The Main ComplianceModule 400 may process the campaign data by electronically associatingthe campaign data with the record for the campaign and digitally storingthe campaign data with the record for the campaign. The campaign datamay be digitally stored as data elements in a database residing in amemory location in the server 120, a peripheral storage device attachedto the server, or one or more storage devices connected to the network(e.g., storage 130). If campaign data inputs have been assigned to oneor more collaborators, but those collaborators have not input the datayet, the Main Compliance Module 400 may, for example through theCommunications Module, sent an electronic message (such as an email)alerting the collaborators and owners that they have not yet suppliedtheir designated portion of campaign data.

III. Privacy Campaign Information Display

At step 430, Main Privacy Compliance Module 400 may, in exemplaryembodiments, call upon a Risk Assessment Module 430 that may determineand assign a Risk Level for the privacy campaign, based wholly or inpart on the information that the owner(s) have input. The RiskAssessment Module 430 will be discussed in more detail below.

At step 432, Main Privacy Compliance Module 400 may in exemplaryembodiments, call upon a Privacy Audit Module 432 that may determine anaudit schedule for each privacy campaign, based, for example, wholly orin part on the campaign data that the owner(s) have input, the RiskLevel assigned to a campaign, and/or any other suitable factors. ThePrivacy Audit Module 432 may also be operable to display the status ofan audit for each privacy campaign. The Privacy Audit Module 432 will bediscussed in more detail below.

At step 435, the Main Privacy Compliance Module 400 may generate anddisplay a GUI showing an inventory page (e.g., inventory page 1500) thatincludes information associated with each campaign. That information mayinclude information input by a user (e.g., one or more owners), orinformation calculated by the Main Privacy Compliance Module 400 orother modules. Such information may include for example, the name of thecampaign, the status of the campaign, the source of the campaign, thestorage location of the personal data related to the campaign, etc. Theinventory page 1500 may also display an indicator representing the RiskLevel (as mentioned, determined for each campaign by the Risk AssessmentModule 430), and audit information related to the campaign that wasdetermined by the Privacy Audit Module (see below). The inventory page1500 may be the landing page displayed to users that access the system.Based on the login information received from the user, the Main PrivacyCompliance Module may determine which campaigns and campaign data theuser is authorized to view, and display only the information that theuser is authorized to view. Also from the inventory page 1500, a usermay add a campaign (discussed above in step 405), view more informationfor a campaign, or edit information related to a campaign (see, e.g.,FIGS. 15, 16, 17).

If other commands from the inventory page are received (e.g., add acampaign, view more information, edit information related to thecampaign), then step 440, 445, and/or 450 may be executed.

At step 440, if a command to view more information has been received ordetected, then at step 445, the Main Privacy Compliance Module 400 maypresent more information about the campaign, for example, on a suitablecampaign information page 1500. At this step, the Main PrivacyCompliance Module 400 may invoke a Data Flow Diagram Module (describedin more detail below). The Data Flow Diagram Module may generate a flowdiagram that shows, for example, visual indicators indicating whetherdata is confidential and/or encrypted (see, e.g., FIG. 1600 below).

At step 450, if the system has received a request to edit a campaign,then, at step 455, the system may display a dialog page that allows auser to edit information regarding the campaign (e.g., edit campaigndialog 1700).

At step 460, if the system has received a request to add a campaign, theprocess may proceed back to step 405.

C. Risk Assessment Module

FIG. 5 illustrates an exemplary process for determining a Risk Level andOverall Risk Assessment for a particular privacy campaign performed byRisk Assessment Module 430.

I. Determining Risk Level

In exemplary embodiments, the Risk Assessment Module 430 may be operableto calculate a Risk Level for a campaign based on the campaign datarelated to the personal data associated with the campaign. The RiskAssessment Module may associate the Risk Level with the record for thecampaign and digitally store the Risk Level with the record for thecampaign.

The Risk Assessment Module 430 may calculate this Risk Level based onany of various factors associated with the campaign. The Risk AssessmentModule 430 may determine a plurality of weighting factors based upon,for example: (1) the nature of the sensitive information collected aspart of the campaign (e.g., campaigns in which medical information,financial information or non-public personal identifying information iscollected may be indicated to be of higher risk than those in which onlypublic information is collected, and thus may be assigned a highernumerical weighting factor); (2) the location in which the informationis stored (e.g., campaigns in which data is stored in the cloud may bedeemed higher risk than campaigns in which the information is storedlocally); (3) the number of individuals who have access to theinformation (e.g., campaigns that permit relatively large numbers ofindividuals to access the personal data may be deemed more risky thanthose that allow only small numbers of individuals to access the data);(4) the length of time that the data will be stored within the system(e.g., campaigns that plan to store and use the personal data over along period of time may be deemed more risky than those that may onlyhold and use the personal data for a short period of time); (5) theindividuals whose sensitive information will be stored (e.g., campaignsthat involve storing and using information of minors may be deemed ofgreater risk than campaigns that involve storing and using theinformation of adults); (6) the country of residence of the individualswhose sensitive information will be stored (e.g., campaigns that involvecollecting data from individuals that live in countries that haverelatively strict privacy laws may be deemed more risky than those thatinvolve collecting data from individuals that live in countries thathave relative lax privacy laws). It should be understood that any othersuitable factors may be used to assess the Risk Level of a particularcampaign, including any new inputs that may need to be added to the riskcalculation.

In particular embodiments, one or more of the individual factors may beweighted (e.g., numerically weighted) according to the deemed relativeimportance of the factor relative to other factors (i.e., Relative RiskRating).

These weightings may be customized from organization to organization,and/or according to different applicable laws. In particularembodiments, the nature of the sensitive information will be weightedhigher than the storage location of the data, or the length of time thatthe data will be stored.

In various embodiments, the system uses a numerical formula to calculatethe Risk Level of a particular campaign. This formula may be, forexample: Risk Level for campaign=(Weighting Factor of Factor1)*(Relative Risk Rating of Factor 1)+(Weighting Factor of Factor2)*(Relative Risk Rating of Factor 2)+(Weighting Factor of FactorN)*(Relative Risk Rating of Factor N). As a simple example, the RiskLevel for a campaign that only collects publicly available informationfor adults and that stores the information locally for a short period ofseveral weeks might be determined as Risk Level=(Weighting Factor ofNature of Sensitive Information)*(Relative Risk Rating of ParticularSensitive Information to be Collected)+(Weighting Factor of Individualsfrom which Information is to be Collected)*(Relative Risk Rating ofIndividuals from which Information is to be Collected)+(Weighting Factorof Duration of Data Retention)*(Relative Risk Rating of Duration of DataRetention)+(Weighting Factor of Individuals from which Data is to beCollected)*(Relative Risk Rating of Individuals from which Data is to beCollected). In this example, the Weighting Factors may range, forexample from 1-5, and the various Relative Risk Ratings of a factor mayrange from 1-10. However, the system may use any other suitable ranges.

In particular embodiments, the Risk Assessment Module 430 may havedefault settings for assigning Overall Risk Assessments to respectivecampaigns based on the numerical Risk Level value determined for thecampaign, for example, as described above. The organization may alsomodify these settings in the Risk Assessment Module 430 by assigning itsown Overall Risk Assessments based on the numerical Risk Level. Forexample, the Risk Assessment Module 430 may, based on default or userassigned settings, designate: (1) campaigns with a Risk Level of 1-7 as“low risk” campaigns, (2) campaigns with a Risk Level of 8-15 as “mediumrisk” campaigns; (3) campaigns with a Risk Level of over 16 as “highrisk” campaigns. As show below, in an example inventory page 1500, theOverall Risk Assessment for each campaign can be indicated by up/downarrow indicators, and further, the arrows may have different shading (orcolor, or portions shaded) based upon this Overall Risk Assessment. Theselected colors may be conducive for viewing by those who suffer fromcolor blindness.

Thus, the Risk Assessment Module 430 may be configured to automaticallycalculate the numerical Risk Level for each campaign within the system,and then use the numerical Risk Level to assign an appropriate OverallRisk Assessment to the respective campaign. For example, a campaign witha Risk Level of 5 may be labeled with an Overall Risk Assessment as “LowRisk”. The system may associate both the Risk Level and the Overall RiskAssessment with the campaign and digitally store them as part of thecampaign record.

II. Exemplary Process for Assessing Risk

Accordingly, as shown in FIG. 5, in exemplary embodiments, the RiskAssessment Module 430 electronically retrieves from a database (e.g.,storage device 130) the campaign data associated with the record for theprivacy campaign. It may retrieve this information serially, or inparallel. At step 505, the Risk Assessment Module 430 retrievesinformation regarding (1) the nature of the sensitive informationcollected as part of the campaign. At step 510, the Risk AssessmentModule 430 retrieves information regarding the (2) the location in whichthe information related to the privacy campaign is stored. At step 515,the Risk Assessment Module 430 retrieves information regarding (3) thenumber of individuals who have access to the information. At step 520,the Risk Assessment Module retrieves information regarding (4) thelength of time that the data associated with a campaign will be storedwithin the System 100. At step 525, the Risk Assessment Module retrievesinformation regarding (5) the individuals whose sensitive informationwill be stored. At step 530, the Risk Assessment Module retrievesinformation regarding (6) the country of residence of the individualswhose sensitive information will be stored.

At step 535, the Risk Assessment Module takes into account any usercustomizations to the weighting factors related to each of the retrievedfactors from steps 505, 510, 515, 520, 525, and 530. At steps 540 and545, the Risk Assessment Module applies either default settings to theweighting factors (which may be based on privacy laws), orcustomizations to the weighting factors. At step 550, the RiskAssessment Module determines a plurality of weighting factors for thecampaign. For example, for the factor related to the nature of thesensitive information collected as part of the campaign, a weightingfactor of 1-5 may be assigned based on whether non-public personalidentifying information is collected.

At step 555, the Risk Assessment Module takes into account any usercustomizations to the Relative Risk assigned to each factor, and at step560 and 565, will either apply default values (which can be based onprivacy laws) or the customized values for the Relative Risk. At step570, the Risk Assessment Module assigns a relative risk rating for eachof the plurality of weighting factors. For example, the relative riskrating for the location of the information of the campaign may beassigned a numerical number (e.g., from 1-10) that is lower than thenumerical number assigned to the Relative Risk Rating for the length oftime that the sensitive information for that campaign is retained.

At step 575, the Risk Assessment Module 430 calculates the relative riskassigned to the campaign based upon the plurality of Weighting Factorsand the Relative Risk Rating for each of the plurality of factors. As anexample, the Risk Assessment Module 430 may make this calculation usingthe formula of Risk Level=(Weighting Factor of Factor 1)*(Relative RiskRating of Factor 1)+(Weighting Factor of Factor 2)*(Relative Risk Ratingof Factor 2)+(Weighting Factor of Factor N)*(Relative Risk Rating ofFactor N).

At step 580, based upon the numerical value derived from step 575, theRisk Assessment Module 430 may determine an Overall Risk Assessment forthe campaign. The Overall Risk Assessment determination may be made forthe privacy campaign may be assigned based on the following criteria,which may be either a default or customized setting: (1) campaigns witha Risk Level of 1-7 as “low risk” campaigns, (2) campaigns with a RiskLevel of 8-15 as “medium risk” campaigns; (3) campaigns with a RiskLevel of over 16 as “high risk” campaigns. The Overall Risk Assessmentis then associated and stored with the campaign record.

D. Privacy Audit Module

The System 100 may determine an audit schedule for each campaign, andindicate, in a particular graphical user interface (e.g., inventory page1500), whether a privacy audit is coming due (or is past due) for eachparticular campaign and, if so, when the audit is/was due. The System100 may also be operable to provide an audit status for each campaign,and alert personnel of upcoming or past due privacy audits. To furtherthe retention of evidence of compliance, the System 100 may also receiveand store evidence of compliance. A Privacy Audit Module 432, mayfacilitate these functions.

I. Determining a Privacy Audit Schedule and Monitoring Compliance

In exemplary embodiments, the Privacy Audit Module 432 is adapted toautomatically schedule audits and manage compliance with the auditschedule. In particular embodiments, the system may allow a user tomanually specify an audit schedule for each respective campaign. ThePrivacy Audit Module 432 may also automatically determine, and save tomemory, an appropriate audit schedule for each respective campaign,which in some circumstances, may be editable by the user.

The Privacy Audit Module 432 may automatically determine the auditschedule based on the determined Risk Level of the campaign. Forexample, all campaigns with a Risk Level less than 10 may have a firstaudit schedule and all campaigns with a Risk Level of 10 or more mayhave a second audit schedule. The Privacy Audit Module may also beoperable determine the audit schedule based on the Overall RiskAssessment for the campaign (e.g., “low risk” campaigns may have a firstpredetermined audit schedule, “medium risk” campaigns may have a secondpredetermined audit schedule, “high risk” campaigns may have a thirdpredetermined audit schedule, etc.).

In particular embodiments, the Privacy Audit Module 432 mayautomatically facilitate and monitor compliance with the determinedaudit schedules for each respective campaign. For example, the systemmay automatically generate one or more reminder emails to the respectiveowners of campaigns as the due date approaches. The system may also beadapted to allow owners of campaigns, or other users, to submit evidenceof completion of an audit (e.g., by for example, submitting screen shotsthat demonstrate that the specified parameters of each campaign arebeing followed). In particular embodiments, the system is configuredfor, in response to receiving sufficient electronic informationdocumenting completion of an audit, resetting the audit schedule (e.g.,scheduling the next audit for the campaign according to a determinedaudit schedule, as determined above).

II. Exemplary Privacy Audit Process

FIG. 6 illustrates an exemplary process performed by a Privacy AuditModule 432 for assigning a privacy audit schedule and facilitating andmanaging compliance for a particular privacy campaign. At step 605, thePrivacy Audit Module 432 retrieves the Risk Level associated with theprivacy campaign. In exemplary embodiments, the Risk Level may be anumerical number, as determined above by the Risk Assessment Module 430.If the organization chooses, the Privacy Audit Module 432 may use theOverall Risk Assessment to determine which audit schedule for thecampaign to assign.

At step 610, based on the Risk Level of the campaign (or the OverallRisk Assessment), or based on any other suitable factor, the PrivacyAudit Module 432 can assign an audit schedule for the campaign. Theaudit schedule may be, for example, a timeframe (i.e., a certain amountof time, such as number of days) until the next privacy audit on thecampaign to be performed by the one or more owners of the campaign. Theaudit schedule may be a default schedule. For example, the Privacy AuditModule can automatically apply an audit schedule of 120 days for anycampaign having Risk Level of 10 and above. These default schedules maybe modifiable. For example, the default audit schedule for campaignshaving a Risk Level of 10 and above can be changed from 120 days to 150days, such that any campaign having a Risk Level of 10 and above isassigned the customized default audit schedule (i.e., 150 days).Depending on privacy laws, default policies, authority overrides, or thepermission level of the user attempting to modify this default, thedefault might not be modifiable.

At step 615, after the audit schedule for a particular campaign hasalready been assigned, the Privacy Audit Module 432 determines if a userinput to modify the audit schedule has been received. If a user input tomodify the audit schedule has been received, then at step 620, thePrivacy Audit Module 432 determines whether the audit schedule for thecampaign is editable (i.e., can be modified). Depending on privacy laws,default policies, authority overrides, or the permission level of theuser attempting to modify the audit schedule, the campaign's auditschedule might not be modifiable.

At step 625, if the audit schedule is modifiable, then the Privacy AuditModule will allow the edit and modify the audit schedule for thecampaign. If at step 620 the Privacy Audit Module determines that theaudit schedule is not modifiable, in some exemplary embodiments, theuser may still request permission to modify the audit schedule. Forexample, the Privacy Audit Module 432 can at step 630 provide anindication that the audit schedule is not editable, but also provide anindication to the user that the user may contact through the system oneor more persons having the authority to grant or deny permission tomodify the audit schedule for the campaign (i.e., administrators) togain permission to edit the field. The Privacy Audit Module 432 maydisplay an on-screen button that, when selected by the user, sends anotification (e.g., an email) to an administrator. The user can thusmake a request to the modify the audit schedule for the campaign in thismanner.

At step 635, the Privacy Audit Module may determine whether permissionhas been granted by an administrator to allow a modification to theaudit schedule. It may make this determination based on whether it hasreceived input from an administrator to allow modification of the auditschedule for the campaign. If the administrator has granted permission,the Privacy Audit Module 432 at step 635 may allow the edit of the auditschedule. If at step 640, a denial of permission is received from theadministrator, or if a certain amount of time has passed (which may becustomized or based on a default setting), the Privacy Audit Module 432retains the audit schedule for the campaign by not allowing anymodifications to the schedule, and the process may proceed to step 645.The Privacy Audit Module may also send a reminder to the administratorthat a request to modify the audit schedule for a campaign is pending.

At step 645, the Privacy Audit Module 432 determines whether a thresholdamount of time (e.g., number of days) until the audit has been reached.This threshold may be a default value, or a customized value. If thethreshold amount of time until an audit has been reached, the PrivacyAudit Module 432 may at step 650 generate an electronic alert. The alertcan be a message displayed to the collaborator the next time thecollaborator logs into the system, or the alert can be an electronicmessage sent to one or more collaborators, including the campaignowners. The alert can be, for example, an email, an instant message, atext message, or one or more of these communication modalities. Forexample, the message may state, “This is a notification that a privacyaudit for Campaign Internet Browsing History is scheduled to occur in 90days.” More than one threshold may be assigned, so that the owner of thecampaign receives more than one alert as the scheduled privacy auditdeadline approaches. If the threshold number of days has not beenreached, the Privacy Audit Module 432 will continue to evaluate whetherthe threshold has been reached (i.e., back to step 645).

In exemplary embodiments, after notifying the owner of the campaign ofan impending privacy audit, the Privacy Audit Module may determine atstep 655 whether it has received any indication or confirmation that theprivacy audit has been completed. In example embodiments, the PrivacyAudit Module allows for evidence of completion to be submitted, and ifsufficient, the Privacy Audit Module 432 at step 660 resets the counterfor the audit schedule for the campaign. For example, a privacy auditmay be confirmed upon completion of required electronic forms in whichone or more collaborators verify that their respective portions of theaudit process have been completed. Additionally, users can submitphotos, screen shots, or other documentation that show that theorganization is complying with that user's assigned portion of theprivacy campaign. For example, a database administrator may take ascreen shot showing that all personal data from the privacy campaign isbeing stored in the proper database and submit that to the system todocument compliance with the terms of the campaign.

If at step 655, no indication of completion of the audit has beenreceived, the Privacy Audit Module 432 can determine at step 665 whetheran audit for a campaign is overdue (i.e., expired). If it is notoverdue, the Privacy Audit Module 432 will continue to wait for evidenceof completion (e.g., step 655). If the audit is overdue, the PrivacyAudit Module 432 at step 670 generates an electronic alert (e.g., anemail, instant message, or text message) to the campaign owner(s) orother administrators indicating that the privacy audit is overdue, sothat the organization can take responsive or remedial measures.

In exemplary embodiments, the Privacy Audit Module 432 may also receivean indication that a privacy audit has begun (not shown), so that thestatus of the audit when displayed on inventory page 1500 shows thestatus of the audit as pending. While the audit process is pending, thePrivacy Audit Module 432 may be operable to generate reminders to besent to the campaign owner(s), for example, to remind the owner of thedeadline for completing the audit.

E. Data Flow Diagram Module

The system 110 may be operable to generate a data flow diagram based onthe campaign data entered and stored, for example in the mannerdescribed above.

I. Display of Security Indicators and Other Information

In various embodiments, a Data Flow Diagram Module is operable togenerate a flow diagram for display containing visual representations(e.g., shapes) representative of one or more parts of campaign dataassociated with a privacy campaign, and the flow of that informationfrom a source (e.g., customer), to a destination (e.g., an internetusage database), to which entities and computer systems have access(e.g., customer support, billing systems). Data Flow Diagram Module mayalso generate one or more security indicators for display. Theindicators may include, for example, an “eye” icon to indicate that thedata is confidential, a “lock” icon to indicate that the data, and/or aparticular flow of data, is encrypted, or an “unlocked lock” icon toindicate that the data, and/or a particular flow of data, is notencrypted. In the example shown in FIG. 16, the dotted arrow linesgenerally depict respective flows of data and the locked or unlockedlock symbols indicate whether those data flows are encrypted orunencrypted. The color of dotted lines representing data flows may alsobe colored differently based on whether the data flow is encrypted ornon-encrypted, with colors conducive for viewing by those who sufferfrom color blindness.

II. Exemplary Process Performed by Data Flow Diagram Module

FIG. 7 shows an example process performed by the Data Flow DiagramModule 700. At step 705, the Data Flow Diagram retrieves campaign datarelated to a privacy campaign record. The campaign data may indicate,for example, that the sensitive information related to the privacycampaign contains confidential information, such as the social securitynumbers of a customer.

At step 710, the Data Flow Diagram Module 700 is operable to displayon-screen objects (e.g., shapes) representative of the Source,Destination, and Access, which indicate that information below theheading relates to the source of the personal data, the storagedestination of the personal data, and access related to the personaldata. In addition to campaign data regarding Source, Destination, andAccess, the Data Flow Diagram Module 700 may also account for userdefined attributes related to personal data, which may also be displayedas on-screen objects. The shape may be, for example, a rectangular box(see, e.g., FIG. 16). At step 715, the Data Flow Diagram Module 700 maydisplay a hyperlink label within the on-screen object (e.g., as shown inFIG. 16, the word “Customer” may be a hyperlink displayed within therectangular box) indicative of the source of the personal data, thestorage destination of the personal data, and access related to thepersonal data, under each of the respective headings. When a user hoversover the hyperlinked word, the Data Flow Diagram is operable to displayadditional campaign data relating to the campaign data associated withthe hyperlinked word. The additional information may also be displayedin a pop up, or a new page. For example, FIG. 16 shows that if a userhovers over the words “Customer,” the Data Flow Diagram Module 700displays what customer information is associated with the campaign(e.g., the Subscriber ID, the IP and Mac Addresses associated with theCustomer, and the customer's browsing and usage history). The Data FlowDiagram Module 700 may also generate for display information relating towhether the source of the data includes minors, and whether consent wasgiven by the source to use the sensitive information, as well as themanner of the consent (for example, through an End User LicenseAgreement (EULA)).

At step 720, the Data Flow Diagram Module 700 may display one or moreparameters related to backup and retention of personal data related tothe campaign, including in association with the storage destination ofthe personal data. As an example, Data Flow Diagram 1615 of FIG. 16displays that the information in the Internet Usage database is backedup, and the retention related to that data is Unknown.

At 725, the Data Flow Diagram Module 700 determines, based on thecampaign data associated with the campaign, whether the personal datarelated to each of the hyperlink labels is confidential. At Step 730, ifthe personal data related to each hyperlink label is confidential, theData Flow Diagram Module 700 generates visual indicator indicatingconfidentiality of that data (e.g., an “eye” icon, as show in Data FlowDiagram 1615). If there is no confidential information for that box,then at step 735, no indicators are displayed. While this is an exampleof the generation of indicators for this particular hyperlink, inexemplary embodiments, any user defined campaign data may visualindicators that may be generated for it.

At step 740, the Data Flow Diagram Module 700 determined whether any ofthe data associated with the source, stored in a storage destination,being used by an entity or application, or flowing to one or moreentities or systems (i.e., data flow) associated with the campaign isdesignated as encrypted. If the data is encrypted, then at step 745 theData Flow Diagram Module 700 may generate an indicator that the personaldata is encrypted (e.g., a “lock” icon). If the data is non-encrypted,then at step 750, the Data Flow Diagram Module 700 displays an indicatorto indicate that the data or particular flow of data is not encrypted.(e.g., an “unlocked lock” icon). An example of a data flow diagram isdepicted in FIG. 9. Additionally, the data flow diagram lines may becolored differently to indicate whether the data flow is encrypted orunencrypted, wherein the colors can still be distinguished by acolor-blind person.

F. Communications Module

In exemplary embodiments, a Communications Module of the System 100 mayfacilitate the communications between various owners and personnelrelated to a privacy campaign. The Communications Module may retaincontact information (e.g., emails or instant messaging contactinformation) input by campaign owners and other collaborators. TheCommunications Module can be operable to take a generated notificationor alert (e.g., alert in step 670 generated by Privacy Audit Module 432)and instantiate an email containing the relevant information. Asmentioned above, the Main Privacy Compliance Module 400 may, for examplethrough a communications module, be operable to send collaboratorsemails regarding their assignment of one or more portions of inputs tocampaign data. Or through the communications module, selecting thecommentators button brings up one or more collaborators that are on-line

In exemplary embodiments, the Communications Module can also, inresponse to a user request (e.g., depressing the “comment” button showin FIG. 9, FIG. 10, FIG. 11, FIG. 12, FIG. 13, FIG. 16), instantiate aninstant messaging session and overlay the instant messaging session overone or more portions of a GUI, including a GUI in which a user ispresented with prompts to enter or select information. An example ofthis instant messaging overlay feature orchestrated by theCommunications Module is shown in FIG. 17. While a real-time messagesession may be generated, off-line users may still able to see themessages when they are back on-line.

The Communications Module may facilitate the generation of alerts thatindicate that one or more emails or instant messages await acollaborator.

If campaign data inputs have been assigned to one or more collaborators,but those collaborators have not input the data yet, the CommunicationsModule, may facilitate the sending of an electronic message (such as anemail) alerting the collaborators and owners that they have not yetsupplied their designated portion of campaign data.

Exemplary User Experience

In the exemplary embodiments of the system for operationalizing privacycompliance, adding a campaign (i.e., data flow) comprises gatheringinformation that includes several phases: (1) a description of thecampaign; (2) the personal data to be collected as part of the campaign;(3) who the personal data relates to; (4) where the personal data bestored; and (5) who will have access to the indicated personal data.

A. FIG. 8: Campaign Record Creation and Collaborator Assignment

FIG. 8 illustrates an example of the first phase of informationgathering to add a campaign. In FIG. 8, a description entry dialog 800may have several fillable/editable fields and drop-down selectors. Inthis example, the user may fill out the name of the campaign in theShort Summary (name) field 805, and a description of the campaign in theDescription field 810. The user may enter or select the name of thebusiness group (or groups) that will be accessing personal data for thecampaign in the Business Group field 815. The user may select theprimary business representative responsible for the campaign (i.e., thecampaign's owner), and designate him/herself, or designate someone elseto be that owner by entering that selection through the Someone Elsefield 820. Similarly, the user may designate him/herself as the privacyoffice representative owner for the campaign, or select someone elsefrom the second Someone Else field 825. At any point, a user assigned asthe owner may also assign others the task of selecting or answering anyquestion related to the campaign. The user may also enter one or moretag words associated with the campaign in the Tags field 830. Afterentry, the tag words may be used to search for campaigns, or used tofilter for campaigns (for example, under Filters 845). The user mayassign a due date for completing the campaign entry, and turn remindersfor the campaign on or off. The user may save and continue, or assignand close.

In example embodiments, some of the fields may be filled in by a user,with suggest-as-you-type display of possible field entries (e.g.,Business Group field 815), and/or may include the ability for the userto select items from a drop-down selector (e.g., drop-down selectors 840a, 840 b, 840 c). The system may also allow some fields to stay hiddenor unmodifiable to certain designated viewers or categories of users.For example, the purpose behind a campaign may be hidden from anyone whois not the chief privacy officer of the company, or the retentionschedule may be configured so that it cannot be modified by anyoneoutside of the organization's' legal department.

B. FIG. 9: Collaborator Assignment Notification and Description Entry

Moving to FIG. 9, in example embodiments, if another businessrepresentative (owner), or another privacy office representative hasbeen assigned to the campaign (e.g., John Doe in FIG. 8), the system maysend a notification (e.g., an electronic notification) to the assignedindividual, letting them know that the campaign has been assigned tohim/her. FIG. 9 shows an example notification 900 sent to John Doe thatis in the form of an email message. The email informs him that thecampaign “Internet Usage Tracking” has been assigned to him, andprovides other relevant information, including the deadline forcompleting the campaign entry and instructions to log in to the systemto complete the campaign (data flow) entry (which may be done, forexample, using a suitable “wizard” program). The user that assigned Johnownership of the campaign may also include additional comments 905 to beincluded with the notification 900. Also included may be an option toreply to the email if an assigned owner has any questions.

In this example, if John selects the hyperlink Privacy Portal 910, he isable to access the system, which displays a landing page 915. Thelanding page 915 displays a Getting Started section 920 to familiarizenew owners with the system, and also displays an “About This Data Flow”section 930 showing overview information for the campaign.

C. FIG. 10: What Personal Data is Collected

Moving to FIG. 10, after the first phase of campaign addition (i.e.,description entry phase), the system may present the user (who may be asubsequently assigned business representative or privacy officer) with adialog 1000 from which the user may enter in the type of personal databeing collected.

In addition, questions are described generally as transitionalquestions, but the questions may also include one or more smartquestions in which the system is configured to: (1) pose an initialquestion to a user and, (2) in response to the user's answer satisfyingcertain criteria, presenting the user with one or more follow-upquestions. For example, in FIG. 10, if the user responds with a choiceto add personal data, the user may be additionally presented follow-upprompts, for example, the select personal data window overlaying screen800 that includes commonly used selections may include, for example,particular elements of an individual's contact information (e.g., name,address, email address), Financial/Billing Information (e.g., creditcard number, billing address, bank account number), Online Identifiers(e.g., IP Address, device type, MAC Address), Personal Details(Birthdate, Credit Score, Location), or Telecommunication Data (e.g.,Call History, SMS History, Roaming Status). The System 100 is alsooperable to pre-select or automatically populate choices—for example,with commonly-used selections 1005, some of the boxes may already bechecked. The user may also use a search/add tool 1010 to search forother selections that are not commonly used and add another selection.Based on the selections made, the user may be presented with moreoptions and fields. For example, if the user selected “Subscriber ID” aspersonal data associated with the campaign, the user may be prompted toadd a collection purpose under the heading Collection Purpose 1015, andthe user may be prompted to provide the business reason why a SubscriberID is being collected under the “Describe Business Need” heading 1020.

D. FIG. 11: Who Personal Data is Collected From

As displayed in the example of FIG. 11, the third phase of adding acampaign may relate to entering and selecting information regarding whothe personal data is gathered from. As noted above, the personal datamay be gathered from, for example, one or more Subjects 100. In theexemplary “Collected From” dialog 1100, a user may be presented withseveral selections in the “Who Is It Collected From” section 1105. Theseselections may include whether the personal data was to be collectedfrom an employee, customer, or other entity. Any entities that are notstored in the system may be added. The selections may also include, forexample, whether the data was collected from a current or prospectivesubject (e.g., a prospective employee may have filled out an employmentapplication with his/her social security number on it). Additionally,the selections may include how consent was given, for example through anend user license agreement (EULA), on-line Opt-in prompt, Impliedconsent, or an indication that the user is not sure. Additionalselections may include whether the personal data was collected from aminor, and where the subject is located.

E. FIG. 12: Where is the Personal Data Stored

FIG. 12 shows an example “Storage Entry” dialog screen 1200, which is agraphical user interface that a user may use to indicate whereparticular sensitive information is to be stored within the system. Fromthis section, a user may specify, in this case for the Internet UsageHistory campaign, the primary destination of the personal data 1220 andhow long the personal data is to be kept 1230. The personal data may behoused by the organization (in this example, an entity called “Acme”) ora third party. The user may specify an application associated with thepersonal data's storage (in this example, ISP Analytics), and may alsospecify the location of computing systems (e.g., servers) that will bestoring the personal data (e.g., a Toronto data center). Otherselections indicate whether the data will be encrypted and/or backed up.

The system also allows the user to select whether the destinationsettings are applicable to all the personal data of the campaign, orjust select data (and if so, which data). In FIG. 12, the user may alsoselect and input options related to the retention of the personal datacollected for the campaign (e.g., How Long Is It Kept 1230). Theretention options may indicate, for example, that the campaign'spersonal data should be deleted after a per-determined period of timehas passed (e.g., on a particular date), or that the campaign's personaldata should be deleted in accordance with the occurrence of one or morespecified events (e.g., in response to the occurrence of a particularevent, or after a specified period of time passes after the occurrenceof a particular event), and the user may also select whether backupsshould be accounted for in any retention schedule. For example, the usermay specify that any backups of the personal data should be deleted (or,alternatively, retained) when the primary copy of the personal data isdeleted.

F. FIG. 13: Who and What Systems have Access to Personal Data

FIG. 13 describes an example Access entry dialog screen 1300. As part ofthe process of adding a campaign or data flow, the user may specify inthe “Who Has Access” section 1305 of the dialog screen 1300. In theexample shown, the Customer Support, Billing, and Government groupswithin the organization are able to access the Internet Usage Historypersonal data collected by the organization. Within each of these accessgroups, the user may select the type of each group, the format in whichthe personal data was provided, and whether the personal data isencrypted. The access level of each group may also be entered. The usermay add additional access groups via the Add Group button 1310.

G. Facilitating Entry of Campaign Data, Including Chat Shown in FIG. 14

As mentioned above, to facilitate the entry of data collected throughthe example GUIs shown in FIGS. 8 through 12, in exemplary embodiments,the system is adapted to allow the owner of a particular campaign (orother user) to assign certain sections of questions, or individualquestions, related to the campaign to contributors other than the owner.This may eliminate the need for the owner to contact other users todetermine information that they don't know and then enter theinformation into the system themselves. Rather, in various embodiments,the system facilitates the entry of the requested information directlyinto the system by the assigned users.

In exemplary embodiments, after the owner assigns a respectiveresponsible party to each question or section of questions that need tobe answered in order to fully populate the data flow, the system mayautomatically contact each user (e.g., via an appropriate electronicmessage) to inform the user that they have been assigned to complete thespecified questions and/or sections of questions, and provide thoseusers with instructions as to how to log into the system to enter thedata. The system may also be adapted to periodically follow up with eachuser with reminders until the user completes the designated tasks. Asdiscussed elsewhere herein, the system may also be adapted to facilitatereal-time text or voice communications between multiple collaborators asthey work together to complete the questions necessary to define thedata flow. Together, these features may reduce the amount of time andeffort needed to complete each data flow.

To further facilitate collaboration, as shown FIG. 14, in exemplaryembodiments, the System 100 is operable to overlay an instant messagingsession over a GUI in which a user is presented with prompts to enter orselect information. In FIG. 14, a communications module is operable tocreate an instant messaging session window 1405 that overlays the Accessentry dialog screen 1400. In exemplary embodiments, the CommunicationsModule, in response to a user request (e.g., depressing the “comment”button show in FIG. 9, FIG. 10, FIG. 11, FIG. 12, FIG. 13, FIG. 16),instantiates an instant messaging session and overlays the instantmessaging session over one or more portions of the GUI.

H: FIG. 15: Campaign Inventory Page

After new campaigns have been added, for example using the exemplaryprocesses explained in regard to FIGS. 8-13, the users of the system mayview their respective campaign or campaigns, depending on whether theyhave access to the campaign. The chief privacy officer, or anotherprivacy office representative, for example, may be the only user thatmay view all campaigns. A listing of all of the campaigns within thesystem may be viewed on, for example, inventory page 1500 (see below).Further details regarding each campaign may be viewed via, for example,campaign information page 1600, which may be accessed by selecting aparticular campaign on the inventory page 1500. And any informationrelated to the campaign may be edited or added through, for example, theedit campaign dialog 1700 screen (see FIG. 17). Certain fields orinformation may not be editable, depending on the particular user'slevel of access. A user may also add a new campaign using a suitableuser interface, such as the graphical user interface shown in FIG. 15 orFIG. 16.

In example embodiments, the System 100 (and more particularly, the MainPrivacy Compliance Module 400) may use the history of past entries tosuggest selections for users during campaign creation and entry ofassociated data. As an example, in FIG. 10, if most entries that containthe term “Internet” and have John Doe as the business rep assigned tothe campaign have the items Subscriber ID, IP Address, and MAC Addressselected, then the items that are commonly used may display aspre-selected items the Subscriber ID, IP address, and MAC Address eachtime a campaign is created having Internet in its description and JohnDoe as its business rep.

FIG. 15 describes an example embodiment of an inventory page 1500 thatmay be generated by the Main Privacy Compliance Module 400. Theinventory page 1500 may be represented in a graphical user interface.Each of the graphical user interfaces (e.g., webpages, dialog boxes,etc.) presented in this application may be, in various embodiments, anHTML-based page capable of being displayed on a web browser (e.g.,Firefox, Internet Explorer, Google Chrome, Opera, etc.), or any othercomputer-generated graphical user interface operable to displayinformation, including information having interactive elements (e.g., aniOS, Mac OS, Android, Linux, or Microsoft Windows application). Thewebpage displaying the inventory page 1500 may include typical featuressuch as a scroll-bar, menu items, as well as buttons for minimizing,maximizing, and closing the webpage. The inventory page 1500 may beaccessible to the organization's chief privacy officer, or any other ofthe organization's personnel having the need, and/or permission, to viewpersonal data.

Still referring to FIG. 15, inventory page 1500 may display one or morecampaigns listed in the column heading Data Flow Summary 1505, as wellas other information associated with each campaign, as described herein.Some of the exemplary listed campaigns include Internet Usage History1510, Customer Payment Information, Call History Log, Cellular RoamingRecords, etc. A campaign may represent, for example, a businessoperation that the organization is engaged in may require the use ofpersonal data, which may include the personal data of a customer. In thecampaign Internet Usage History 1510, for example, a marketingdepartment may need customers' on-line browsing patterns to runanalytics. Examples of more information that may be associated with theInternet Usage History 1510 campaign will be presented in FIG. 4 andFIG. 5. In example embodiments, clicking on (i.e., selecting) the columnheading Data Flow Summary 1505 may result in the campaigns being sortedeither alphabetically, or reverse alphabetically.

The inventory page 1500 may also display the status of each campaign, asindicated in column heading Status 1515. Exemplary statuses may include“Pending Review”, which means the campaign has not been approved yet,“Approved,” meaning the data flow associated with that campaign has beenapproved, “Audit Needed,” which may indicate that a privacy audit of thepersonal data associated with the campaign is needed, and “ActionRequired,” meaning that one or more individuals associated with thecampaign must take some kind of action related to the campaign (e.g.,completing missing information, responding to an outstanding message,etc.). In certain embodiments, clicking on (i.e., selecting) the columnheading Status 1515 may result in the campaigns being sorted by status.

The inventory page 1500 of FIG. 15 may list the “source” from which thepersonal data associated with a campaign originated, under the columnheading “Source” 1520. The sources may include one or more of thesubjects 100 in example FIG. 1. As an example, the campaign “InternetUsage History” 1510 may include a customer's IP address or MAC address.For the example campaign “Employee Reference Checks”, the source may bea particular employee. In example embodiments, clicking on (i.e.,selecting) the column heading Source 1520 may result in the campaignsbeing sorted by source.

The inventory page 1500 of FIG. 15 may also list the “destination” ofthe personal data associated with a particular campaign under the columnheading Destination 1525. Personal data may be stored in any of avariety of places, for example on one or more storage devices 280 thatare maintained by a particular entity at a particular location.Different custodians may maintain one or more of the different storagedevices. By way of example, referring to FIG. 15, the personal dataassociated with the Internet Usage History campaign 1510 may be storedin a repository located at the Toronto data center, and the repositorymay be controlled by the organization (e.g., Acme corporation) oranother entity, such as a vendor of the organization that has been hiredby the organization to analyze the customer's internet usage history.Alternatively, storage may be with a department within the organization(e.g., its marketing department). In example embodiments, clicking on(i.e., selecting) the column heading Destination 1525 may result in thecampaigns being sorted by destination.

On the inventory page 1500, the Access heading 1530 may show the numberof transfers that the personal data associated with a campaign hasundergone. In example embodiments, clicking on (i.e., selecting) thecolumn heading “Access” 1530 may result in the campaigns being sorted byAccess.

The column with the heading Audit 1535 shows the status of any privacyaudits associated with the campaign. Privacy audits may be pending, inwhich an audit has been initiated but yet to be completed. The auditcolumn may also show for the associated campaign how many days havepassed since a privacy audit was last conducted for that campaign.(e.g., 140 days, 360 days). If no audit for a campaign is currentlyrequired, an “OK” or some other type of indication of compliance (e.g.,a “thumbs up” indicia) may be displayed for that campaign's auditstatus. Campaigns may also be sorted based on their privacy audit statusby selecting or clicking on the Audit heading 1535.

In example inventory page 1500, an indicator under the heading Risk 1540may also display an indicator as to the Risk Level associated with thepersonal data for a particular campaign. As described earlier, a riskassessment may be made for each campaign based on one or more factorsthat may be obtained by the system. The indicator may, for example, be anumerical score (e.g., Risk Level of the campaign), or, as in theexample shown in FIG. 15, it may be arrows that indicate the OverallRisk Assessment for the campaign. The arrows may be of different shades,or different colors (e.g., red arrows indicating “high risk” campaigns,yellow arrows indicating “medium risk” campaigns, and green arrowsindicating “low risk” campaigns). The direction of the arrows—forexample, pointing upward or downward, may also provide a quickindication of Overall Risk Assessment for users viewing the inventorypage 1500. Each campaign may be sorted based on the Risk Levelassociated with the campaign.

The example inventory page 1500 may comprise a filter tool, indicated byFilters 1545, to display only the campaigns having certain informationassociated with them. For example, as shown in FIG. 15, under CollectionPurpose 1550, checking the boxes “Commercial Relations,” “ProvideProducts/Services”, “Understand Needs,” “Develop Business & Ops,” and“Legal Requirement” will result the display under the Data Flow Summary1505 of only the campaigns that meet those selected collection purposerequirements.

From example inventory page 1500, a user may also add a campaign byselecting (i.e., clicking on) Add Data Flow 1555. Once this selectionhas been made, the system initiates a routine to guide the user in aphase-by-phase manner through the process of creating a new campaign(further details herein). An example of the multi-phase GUIs in whichcampaign data associated with the added privacy campaign may be inputand associated with the privacy campaign record is described in FIG.8-13 above.

From the example inventory page 1500, a user may view the informationassociated with each campaign in more depth, or edit the informationassociated with each campaign. To do this, the user may, for example,click on or select the name of the campaign (i.e., click on InternetUsage History 1510). As another example, the user may select a buttondisplayed on screen indicating that the campaign data is editable (e.g.,edit button 1560).

I: FIG. 16: Campaign Information Page and Data Flow Diagram

FIG. 16 shows an example of information associated with each campaignbeing displayed in a campaign information page 1600. Campaigninformation page 1600 may be accessed by selecting (i.e., clicking on),for example, the edit button 1560. In this example, Personal DataCollected section 1605 displays the type of personal data collected fromthe customer for the campaign Internet Usage History. The type ofpersonal data, which may be stored as data elements associated with theInternet Usage History campaign digital record entry. The type ofinformation may include, for example, the customer's Subscriber ID,which may be assigned by the organization (e.g., a customeridentification number, customer account number). The type of informationmay also include data associated with a customer's premises equipment,such as an IP Address, MAC Address, URL History (i.e., websitesvisited), and Data Consumption (i.e., the number of megabytes orgigabytes that the user has download).

Still referring to FIG. 16, the “About this Data Flow” section 1610displays relevant information concerning the campaign, such as thepurpose of the campaign. In this example, a user may see that theInternet Usage History campaign is involved with the tracking ofinternet usage from customers in order to bill appropriately, manageagainst quotas, and run analytics. The user may also see that thebusiness group that is using the sensitive information associated withthis campaign is the Internet group. A user may further see that thenext privacy audit is scheduled for Jun. 10, 2016, and that the lastupdate of the campaign entry was Jan. 2, 2015. The user may also selectthe “view history” hyperlink to display the history of the campaign.

FIG. 16 also depicts an example of a Data Flow Diagram 1615 generated bythe system, based on information provided for the campaign. The DataFlow Diagram 1615 may provide the user with a large amount ofinformation regarding a particular campaign in a single compact visual.In this example, for the campaign Internet Usage History, the user maysee that the source of the personal data is the organization'scustomers. In example embodiments, as illustrated, hovering the cursor(e.g., using a touchpad, or a mouse) over the term “Customers” may causethe system to display the type of sensitive information obtained fromthe respective consumers, which may correspond with the informationdisplayed in the “Personal Data Collected” section 1605.

In various embodiments, the Data Flow Diagram 1615 also displays thedestination of the data collected from the User (in this example, anInternet Usage Database), along with associated parameters related tobackup and deletion. The Data Flow Diagram 1615 may also display to theuser which department(s) and what system(s) have access to the personaldata associated with the campaign. In this example, the Customer SupportDepartment has access to the data, and the Billing System may retrievedata from the Internet Usage Database to carry out that system'soperations. In the Data Flow Diagram 1615, one or more securityindicators may also be displayed. The may include, for example, an “eye”icon to indicate that the data is confidential, a “lock” icon toindicate that the data, and/or a particular flow of data, is encrypted,or an “unlocked lock” icon to indicate that the data, and/or aparticular flow of data, is not encrypted. In the example shown in FIG.16, the dotted arrow lines generally depict respective flows of data andthe locked or unlocked lock symbols indicate whether those data flowsare encrypted or unencrypted.

Campaign information page 1600 may also facilitate communications amongthe various personnel administrating the campaign and the personal dataassociated with it. Collaborators may be added through the Collaboratorsbutton 1625. The system may draw information from, for example, anactive directory system, to access the contact information ofcollaborators.

If comment 1630 is selected, a real-time communication session (e.g., aninstant messaging session) among all (or some) of the collaborators maybe instantiated and overlaid on top of the page 1600. This may behelpful, for example, in facilitating population of a particular page ofdata by multiple users. In example embodiments, the Collaborators 1625and Comments 1630 button may be included on any graphical user interfacedescribed herein, including dialog boxes in which information is enteredor selected. Likewise, any instant messaging session may be overlaid ontop of a webpage or dialog box. The system may also use the contactinformation to send one or more users associated with the campaignperiodic updates, or reminders. For example, if the deadline to finishentering the campaign data associated with a campaign is upcoming inthree days, the business representative of that assigned campaign may besent a message reminding him or her that the deadline is in three days.

Like inventory page 1500, campaign information page 1600 also allows forcampaigns to be sorted based on risk (e.g., Sort by Risk 1635). Thus,for example, a user is able to look at the information for campaignswith the highest risk assessment.

J: FIG. 17: Edit Campaign Dialog

FIG. 17 depicts an example of a dialog box—the edit campaign dialog1000. The edit campaign dialog 1000 may have editable fields associatedwith a campaign. In this example, the information associated with theInternet Usage History campaign 310 may be edited via this dialog. Thisincludes the ability for the user to change the name of the campaign,the campaign's description, the business group, the current owner of thecampaign, and the particular personal data that is associated with thecampaign (e.g., IP address, billing address, credit score, etc.). Inexample embodiments, the edit campaign dialog 1000 may also allow forthe addition of more factors, checkboxes, users, etc.

The system 100 also includes a Historical Record Keeping Module, whereinevery answer, change to answer, as well as assignment/re-assignment ofowners and collaborators is logged for historical record keeping.

Automated Approach to Demonstrating Privacy by Design, and Integrationwith Software Development and Agile Tools for Privacy Design

In particular embodiments, privacy by design, which is a documentedapproach to managing privacy risks, can be used in the design phase of aproduct (e.g., a hardware or software product, and/or anelectromechanical product that is controlled by software). In variousembodiments, the system is adapted to automate this process by: (1)facilitating the completion of an initial privacy impact assessment fora product; (2) facilitating the completion of a gap analysis andidentification of recommended steps for addressing any privacy-relatedconcerns identified in the initial privacy impact assessment; and (3)automatically conducting a revised privacy impact assessment after therecommended steps have been completed. The system then documents thisprocess, for example, for the purpose of verifying the relevantorganization's use of privacy-by-design in its day-to-day businesspractices. These steps above are discussed in greater detail below.

Initial Assessment

In various embodiments, when a business team within a particularorganization is planning to begin a privacy campaign, the systempresents the business team with a set of assessment questions that aredesigned to help one or more members of the organization's privacy teamto understand what the business team's plans are, and to understandwhether the privacy campaign may have a privacy impact on theorganization. The questions may also include a request for the businessteam to provide the “go-live” date, or implementation date, for theprivacy campaign. In response to receiving the answers to thesequestions, the system stores the answers to the system's memory andmakes the answers available to the organization's privacy team. Thesystem may also add the “go-live” date to one or more electroniccalendars (e.g., the system's electronic docket).

In some implementations, the initial assessment can include an initialprivacy impact assessment that evaluates one or more privacy impactfeatures of the proposed design of the product. The initial privacyimpact assessment incorporates the respective answers for the pluralityof question/answer pairings in the evaluation of the one or more privacyimpact features. The privacy impact features may, for example, berelated to how the proposed design of the new product will collect, use,store, and/or manage personal data. One or more of these privacy impactfeatures can be evaluated, and the initial privacy assessment can beprovided to identify results of the evaluation.

Gap Analysis/Recommended Steps

After the system receives the answers to the questions, one or moremembers of the privacy team may review the answers to the questions. Theprivacy team may then enter, into the system, guidance and/orrecommendations regarding the privacy campaign. In some implementations,the privacy team may input their recommendations into the privacycompliance software. In particular embodiments, the system automaticallycommunicates the privacy team's recommendations to the business teamand, if necessary, reminds one or more members of the business team toimplement the privacy team's recommendations before the go-live date.The system may also implement one or more audits (e.g., as describedabove) to make sure that the business team incorporates the privacyteam's recommendations before the “go-live” date.

The recommendations may include one or more recommended steps that canbe related to modifying one or more aspects of how the product willcollect, use, store, and/or manage personal data. The recommended stepsmay include, for example: (1) limiting the time period that personaldata is held by the system (e.g., seven days); (2) requiring thepersonal data to be encrypted when communicated or stored; (3)anonymizing personal data; or (4) restricting access to personal data toa particular, limited group of individuals. The one or more recommendedsteps may be provided to address a privacy concern with one or more ofthe privacy impact features that were evaluated in the initial privacyimpact assessment.

In response to a recommended one or more steps being provided (e.g., bythe privacy compliance officers), the system may generate one or moretasks in suitable project management software that is used in managingthe proposed design of the product at issue. In various embodiments, theone or more tasks may be tasks that, if recommended, would individuallyor collectively complete one or more (e.g., all of) the recommendedsteps. For example, if the one or more recommended steps includerequiring personal data collected by the product to be encrypted, thenthe one or more tasks may include revising the product so that itencrypts any personal data that it collects.

The one or more tasks may include, for example, different steps to beperformed at different points in the development of the product. Inparticular embodiments, the computer software application may alsomonitor, either automatically or through suitable data inputs, thedevelopment of the product to determine whether the one or more taskshave been completed.

Upon completion of each respective task in the one or more tasks, thesystem may provide a notification that the task has been completed. Forexample, the project management software may provide a suitablenotification to the privacy compliance software that the respective taskhas been completed.

Final/Updated Assessment

Once the mitigation steps and recommendations are complete, the systemmay (e.g., automatically) conduct an updated review to assess anyprivacy risks associated with the revised product.

In particular embodiments, the system includes unique reporting andhistorical logging capabilities to automate Privacy-by-Design reportingand/or privacy assessment reporting. In various embodiments, the systemis adapted to: (1) measure/analyze the initial assessment answers fromthe business team; (2) measure recommendations for the privacy campaign;(3) measure any changes that were implemented prior to the go-live date;(4) automatically differentiate between: (a) substantive privacyprotecting changes, such as the addition of encryption, anonymization,or minimizations; and (b) non-substantive changes, such as spellingcorrection.

Reporting Functionality

The system may also be adapted to generate a privacy assessment reportshowing that, in the course of a business's normal operations: (1) thebusiness evaluates projects prior to go-live for compliance with one ormore privacy-related regulations or policies; and (2) relatedsubstantive recommendations are made and implemented prior to go-live.This may be useful in documenting that privacy-by-design is beingeffectively implemented for a particular privacy campaign.

The privacy assessment report may, in various embodiments, include anupdated privacy impact assessment that evaluates the one or more privacyimpact features after the one or more recommended steps discussed aboveare implemented. The system may generate this updated privacy impactassessment automatically by, for example, automatically modifying anyanswers from within the question/answer pairings of the initial privacyimpact assessment to reflect any modifications to the product that havebeen made in the course of completing the one or more tasks thatimplement the one or more substantive recommendations. For example, if aparticular question from the initial privacy impact assessment indicatedthat certain personal data was personally identifiable data, and arecommendation was made to anonymize the data, the question/answerpairing for the particular question could be revised so the answer tothe question indicates that the data has been anonymized. Any revisedquestion/answer pairings may then be used to complete an updated privacyimpact assessment and related report.

FIGS. 18A and 18B show an example process performed by a Data PrivacyCompliance Module 1800. In executing the Data Privacy Compliance Module1800, the system begins at Step 1802, where it presents a series ofquestions to a user (e.g., via a suitable computer display screen orother user-interface, such as a voice-interface) regarding the designand/or anticipated operation of the product. This may be done, forexample, by having a first software application (e.g., a data privacysoftware application or other suitable application) present the userwith a template of questions regarding the product (e.g., for use inconducting an initial privacy impact assessment for the product). Suchquestions may include, for example, data mapping questions and otherquestions relevant to the product's design and/or anticipated operation.

Next, the at Step 1804, the system receives, via a first computersoftware application, from a first set of one or more users (e.g.,product designers, such as software designers, or other individuals whoare knowledgeable about the product), respective answers to thequestions regarding the product and associates the respective answerswith their corresponding respective questions within memory to create aplurality of question/answer pairings regarding the proposed design ofthe product (e.g., software, a computerized electro-mechanical product,or other product).

Next, at Step 1806, the system presents a question to one or more usersrequesting the scheduled implantation date for the product. At Step1808, the system receives this response and saves the scheduledimplementation date to memory.

Next, after receiving the respective answers at Step 1804, the systemdisplays, at Step 1810, the respective answers (e.g., along with theirrespective questions and/or a summary of the respective questions) to asecond set of one or more users (e.g., one or more privacy officers fromthe organization that is designing the product), for example, in theform a plurality of suitable question/answer pairings. As an aside,within the context of this specification, pairings of an answer andeither its respective question or a summary of the question may bereferred to as a “question/answer” pairing. As an example, the question“Is the data encrypted? and respective answer “Yes” may be represented,for example, in either of the following question/answer pairings: (1)“The data is encrypted”; and (2) “Data encrypted? Yes”. Alternatively,the question/answer pairing may be represented as a value in aparticular field in a data structure that would convey that the data atissue is encrypted.

The system then advances to Step 1812, where it receives, from thesecond set of users, one or more recommended steps to be implemented aspart of the proposed design of the product and before the implementationdate, the one or more recommended steps comprising one or more stepsthat facilitate the compliance of the product with the one or moreprivacy standards and/or policies. In particular embodiments in whichthe product is a software application or an electro-mechanical devicethat runs device software, the one or more recommended steps maycomprise modifying the software application or device software to complywith one or more privacy standards and/or policies.

Next, at Step 1814, in response to receiving the one or more recommendedsteps, the system automatically initiates the generation of one or moretasks in a second computer software application (e.g., projectmanagement software) that is to be used in managing the design of theproduct. In particular embodiments, the one or more tasks comprise oneor more tasks that, if completed, individually and/or collectively wouldresult in the completion of the one or more recommended steps. Thesystem may do this, for example, by facilitating communication betweenthe first and second computer software applications via a suitableapplication programming interface (API).

The system then initiates a monitoring process for determining whetherthe one or more tasks have been completed. This step may, for example,be implemented by automatically monitoring which changes (e.g., edits tosoftware code) have been made to the product, or by receiving manualinput confirming that various tasks have been completed.

Finally, at Step 1816, at least partially in response to the firstcomputer software application being provided with the notification thatthe task has been completed, the system generates an updated privacyassessment for the product that reflects the fact that the task has beencompleted. The system may generate this updated privacy impactassessment automatically by, for example, automatically modifying anyanswers from within the question/answer pairings of the initial impactprivacy assessment to reflect any modifications to the product that havebeen made in the course of completing the one or more tasks thatimplement the one or more substantive recommendations. For example, if aparticular question from the initial privacy impact assessment indicatedthat certain personal data was personally-identifiable data, and arecommendation was made to anonymize the data, the question/answerpairing for the particular question could be revised so that the answerto the question indicates that the data has been anonymized. Any revisedquestion/answer pairings may then be used to complete an updated privacyassessment report.

FIGS. 19A-19B depict the operation of a Privacy-By-Design Module 1900.In various embodiments, when the system executes the Privacy-By-DesignModule 1900, the system begins, at Step 1902, where it presents a seriesof questions to a user (e.g., via a suitable computer display screen orother user-interface, such as a voice-interface) regarding the designand/or anticipated operation of the product. This may be done, forexample, by having a first software application (e.g., a data privacysoftware application or other suitable application) present the userwith a template of questions regarding the product (e.g., for use inconducting an initial privacy impact assessment for the product). Suchquestions may include, for example, data mapping questions and otherquestions relevant to the product's design and/or anticipated operation.

Next, the at Step 1904, the system receives, e.g., via a first computersoftware application, from a first set of one or more users (e.g.,product designers, such as software designers, or other individuals whoare knowledgeable about the product), respective answers to thequestions regarding the product and associates the respective answerswith their corresponding respective questions within memory to create aplurality of question/answer pairings regarding the proposed design ofthe product (e.g., software, a computerized electro-mechanical product,or other product).

Next, at Step 1906, the system presents a question to one or more usersrequesting the scheduled implantation date for the product. At Step1908, the system receives this response and saves the scheduledimplementation date to memory.

Next, after receiving the respective answers at Step 1904, the systemdisplays, at Step 1910, the respective answers (e.g., along with theirrespective questions and/or a summary of the respective questions) to asecond set of one or more users (e.g., one or more privacy officers fromthe organization that is designing the product), for example, in theform a plurality of suitable question/answer pairings. As an aside,within the context of this specification, pairings of an answer andeither its respective question or a summary of the question may bereferred to as a “question/answer” pairing. As an example, the question“Is the data encrypted? and respective answer “Yes” may be represented,for example, in either of the following question/answer pairings: (1)“The data is encrypted”; and (2) “Data encrypted? Yes”. Alternatively,the question/answer pairing may be represented as a value in aparticular field in a data structure that would convey that the data atissue is encrypted.

The system then advances to Step 1912, where it receives, from thesecond set of users, one or more recommended steps to be implemented aspart of the proposed design of the product and before the implementationdate, the one or more recommended steps comprising one or more stepsthat facilitate the compliance of the product with the one or moreprivacy standards and/or policies. In particular embodiments in whichthe product is a software application or an electro-mechanical devicethat runs device software, the one or more recommended steps maycomprise modifying the software application or device software to complywith one or more privacy standards and/or policies.

Next, at Step 1914, in response to receiving the one or more recommendedsteps, the system automatically initiates the generation of one or moretasks in a second computer software application (e.g., projectmanagement software) that is to be used in managing the design of theproduct. In particular embodiments, the one or more tasks comprise oneor more tasks that, if completed, individually and/or collectively wouldresult in the completion of the one or more recommended steps.

The system then initiates a monitoring process for determining whetherthe one or more tasks have been completed. This step may, for example,be implemented by automatically monitoring which changes (e.g., edits tosoftware code) have been made to the product, or by receiving manualinput confirming that various tasks have been completed.

The system then advances to Step 1916, where it receives a notificationthat the at least one task has been completed. Next, at Step 1918, atleast partially in response to the first computer software applicationbeing provided with the notification that the task has been completed,the system generates an updated privacy assessment for the product thatreflects the fact that the task has been completed. The system maygenerate this updated privacy impact assessment automatically by, forexample, automatically modifying any answers from within thequestion/answer pairings of the initial impact privacy assessment toreflect any modifications to the product that have been made in thecourse of completing the one or more tasks that implement the one ormore substantive recommendations. For example, if a particular questionfrom the initial privacy impact assessment indicated that certainpersonal data was personally-identifiable data, and a recommendation wasmade to anonymize the data, the question/answer pairing for theparticular question could be revised so that the answer to the questionindicates that the data has been anonymized. Any revised question/answerpairings may then be used to complete an updated privacy assessmentreport.

As discussed above, the system may then analyze the one or morerevisions that have made to the product to determine whether the one ormore revisions substantively impact the product's compliance with one ormore privacy standards. Finally, the system generates aprivacy-by-design report that may, for example, include a listing of anyof the one or more revisions that have been made and that substantivelyimpact the product's compliance with one or more privacy standards.

In various embodiments, the privacy-by-design report may also comprise,for example, a log of data demonstrating that the business, in thenormal course of its operations: (1) conducts privacy impact assessmentson new products before releasing them; and (2) implements any changesneeded to comply with one or more privacy polies before releasing thenew products. Such logs may include data documenting the results of anyprivacy impact assessments conducted by the business (and/or anyparticular sub-part of the business) on new products before eachrespective new product's launch date, any revisions that the business(and/or any particular sub-part of the business) make to new productsbefore the launch of the product. The report may also optionally includethe results of any updated privacy impact assessments conducted onproducts after the products have been revised to comply with one or moreprivacy regulations and/or policies. The report may further include alisting of any changes that the business has made to particular productsin response to initial impact privacy assessment results for theproducts. The system may also list which of the listed changes weredetermined, by the system, to be substantial changes (e.g., that thechanges resulted in advancing the product's compliance with one or moreprivacy regulations).

Additional Aspects of System

1. Standardized and Customized Assessment of Vendors' Compliance withPrivacy and/or Security Policies

In particular embodiments, the system may be adapted to: (1) facilitatethe assessment of one or more vendors' compliance with one or moreprivacy and/or security policies; and (2) allow organizations (e.g.,companies or other organizations) who do business with the vendors tocreate, view and/or apply customized criteria to informationperiodically collected by the system to evaluate each vendor'scompliance with one or more of the company's specific privacy and/orsecurity policies. In various embodiments, the system may also flag anyassessments, projects, campaigns, and/or data flows that theorganization has documented and maintained within the system if thosedata flows are associated with a vendor that has its rating changed sothat the rating meets certain criteria (e.g., if the vendor's ratingfalls below a predetermined threshold).

In particular embodiments:

-   -   The system may include an online portal and community that        includes a listing of all supported vendors.    -   An appropriate party (e.g., the participating vendor or a member        of the on-line community) may use the system to submit an        assessment template that is specific to a particular vendor.        -   If the template is submitted by the vendor itself, the            template may be tagged in any appropriate way as “official”        -   An instance for each organization using the system (i.e.,            customer) is integrated with this online community/portal so            that the various assessment templates can be directly fed            into that organization's instance of the system if the            organization wishes to use it.    -   Vendors may subscribe to a predetermined standardized assessment        format.        -   Assessment results may also be stored in the central            community/portal.        -   A third-party privacy and/or security policy compliance            assessor, on a schedule, may (e.g., periodically) complete            the assessment of the vendor.        -   Each organization using the system can subscribe to the            results (e.g., once they are available).        -   Companies can have one or more customized rules set up            within the system for interpreting the results of            assessments in their own unique way. For example:            -   Each customer can weight each question within an                assessment as desired and set up addition/multiplication                logic to determine an aggregated risk score that takes                into account the customized weightings given to each                question within the assessment.            -   Based on new assessment results—the system may notify                each customer if the vendor's rating falls, improves, or                passes a certain threshold.            -   The system can flag any assessments, projects,                campaigns, and/or data flows that the customer has                documented and maintained within the system if those                data flows are associated with a vendor that has its                rating changed.                2. Privacy Policy Compliance System that Facilitates                Communications with Regulators (Including Translation                Aspect)

In particular embodiments, the system is adapted to interface with thecomputer systems of regulators (e.g., government regulatory agencies)that are responsible for approving privacy campaigns. This may, forexample, allow the regulators to review privacy campaign informationdirectly within particular instances of the system and, in someembodiments, approve the privacy campaigns electronically.

In various embodiments, the system may implement this concept by:

-   -   Exporting relevant data regarding the privacy campaign, from an        organization's instance of the system (e.g., customized version        of the system) in standardized format (e.g., PDF or Word) and        sending the extracted data to an appropriate regulator for        review (e.g., in electronic or paper format).        -   Either regular provides the format that the system codes to,            or the organization associated with the system provides a            format that the regulators are comfortable with.    -   Send secure link to regulator that gives them access to comment        and leave feedback        -   Gives the regulator direct access to the organization's            instance of the system with a limited and restricted view of            just the projects and associated audit and commenting logs            the organization needs reviewed.        -   Regulator actions are logged historically and the regulator            can leave guidance, comments, and questions, etc.    -   Have portal for regulator that securely links to the systems of        their constituents.

Details:

-   -   When submitted—the PIAs are submitted with requested        priority—standard or expedited.    -   DPA specifies how many expedited requests individuals are        allowed to receive.    -   Either the customer or DPA can flag a PIA or associated        comments/guidance on the PIA with “needs translation” and that        can trigger an automated or manual language translation.    -   Regulator could be a DPA “data protection authority” in any EU        country, or other country with similar concept like FTC in US,        or OPC in Canada.        3. Systems/Methods for Measuring the Privacy Maturity of a        Business Group within an Organization.

In particular embodiments, the system is adapted for automaticallymeasuring the privacy of a business group, or other group, within aparticular organization that is using the system. This may provide anautomated way of measuring the privacy maturity, and one or more trendsof change in privacy maturity of the organization, or a selectedsub-group of the organization.

In various embodiments, the organization using the system can customizeone or more algorithms used by the system to measure the privacymaturity of a business group (e.g., by specifying one or more variablesand/or relative weights for each variable in calculating a privacymaturity score for the group). The following are examples of variablesthat may be used in this process:

-   -   Issues/Risks found in submitted assessments that are unmitigated        or uncaught prior to the assessment being submitted to the        privacy office        -   % of privacy assessments with high issues/total assessments        -   % with medium        -   % with low    -   Size and type of personal data used by the group        -   Total assessments done        -   Number of projects/campaigns with personal data        -   Amount of personal data        -   Volume of data transfers to internal and external parties    -   Training of the people in the group        -   Number or % of individuals who have watched training,            readings, or videos        -   Number or % of individuals who have completed quizzes or            games for privacy training        -   Number or % of individuals who have attended privacy events            either internally or externally        -   Number or % of individuals who are members of IAPP        -   Number or % of individuals who have been specifically            trained in privacy either internally or externally, formally            (IAPP certification) or informally        -   Usage of an online version of the system, or mobile training            or communication portal that customer has implemented    -   Other factors        4. Automated Assessment of Compliance (Scan App or Website to        Determine Behavior/Compliance with Privacy Policies)

In various embodiments, instead of determining whether an organizationcomplies with the defined parameters of a privacy campaign by, forexample, conducting an audit as described above (e.g., by asking usersto answer questions regarding the privacy campaign, such as “What iscollected” “what cookies are on your website”, etc.), the system may beconfigured to automatically determine whether the organization iscomplying with one or more aspects of the privacy policy.

For example, during the audit process, the system may obtain a copy of asoftware application (e.g., an “app”) that is collecting and/or usingsensitive user information, and then automatically analyze the app todetermine whether the operation of the app is complying with the termsof the privacy campaign that govern use of the app.

Similarly, the system may automatically analyze a website that iscollecting and/or using sensitive user information to determine whetherthe operation of the web site is complying with the terms of the privacycampaign that govern use of the web site.

In regard to various embodiments of the automatic application-analyzingembodiment referenced above:

-   -   The typical initial questions asked during an audit may be        replaced by a request to “Upload your app here”.        -   After the app is uploaded to the system, the system detects            what privacy permissions and data the app is collecting from            users.        -   This is done by having the system use static or behavioral            analysis of the application, or by having the system            integrate with a third-party system or software (e.g.,            Veracode), which executes the analysis.        -   During the analysis of the app, the system may detect, for            example, whether the app is using location services to            detect the location of the user's mobile device.        -   In response to determining that the app is collecting one or            more specified types of sensitive information (e.g., the            location of the user's mobile device), the system may            automatically request follow up information from the user by            posing one or more questions to the user, such as:            -   For what business reason is the data being collected?            -   How is the user's consent given to obtain the data?            -   Would users be surprised that the data is being                collected?            -   Is the data encrypted at rest and/or in motion?            -   What would happen if the system did not collect this                data? What business impact would it have?            -   In various embodiments, the system is adapted to allow                each organization to define these follow-up questions,                but the system asks the questions (e.g., the same                questions, or a customized list of questions) for each                privacy issue that is found in the app.        -   In various embodiments, after a particular app is scanned a            first time, when the app is scanned, the system may only            detect and analyze any changes that have been made to the            app since the previous scan of the app.        -   In various embodiments, the system is adapted to            (optionally) automatically monitor (e.g., continuously            monitor) one or more online software application            marketplaces (such as Microsoft, Google, or Apple's App            Store) to determine whether the application has changed. If            so, the system may, for example: (1) automatically scan the            application as discussed above; and (2) automatically notify            one or more designated individuals (e.g., privacy office            representatives) that an app was detected that the business            failed to perform a privacy assessment on prior to launching            the application.

In regard to various embodiments of the automatic application-analyzingembodiment referenced above:

-   -   The system prompts the user to enter the URL of the website to        be analyzed, and, optionally, the URL to the privacy policy that        applies to the web site.    -   The system then scans the website for cookies, and/or other        tracking mechanisms, such as fingerprinting technologies and/or        3rd party SDKs.        -   The system may then optionally ask the user to complete a            series of one or more follow-up questions for each of these            items found during the scan of the website.        -   This may help the applicable privacy office craft a privacy            policy to be put on the website to disclose the use of the            tracking technologies and SDK's used on the website.    -   The system may then start a continuous monitoring of the web        site site to detect whether any new cookies, SDKs, or tracking        technologies are used. In various embodiments, the system is        configured to, for example, generate an alert to an appropriate        individual (e.g., a designated privacy officer) to inform them        of the change to the website. The privacy officer may use this        information, for example, to determine whether to modify the        privacy policy for the website or to coordinate discontinuing        use of the new tracking technologies and/or SDK's.    -   In various embodiments, the system may also auto-detect whether        any changes have been made to the policy or the location of the        privacy policy link on the page and, in response to        auto-detecting such changes, trigger an audit of the project.    -   It should be understood that the above methods of automatically        assessing behavior and/or compliance with one or more privacy        policies may be done in any suitable way (e.g., ways other than        website scanning and app scanning). For example, the system may        alternatively, or in addition, automatically detect, scan and/or        monitor any appropriate technical system(s) (e.g., computer        system and/or system component or software), cloud services,        apps, websites and/or data structures, etc.        5. System Integration with DLP Tools.

Overview

DLP tools are traditionally used by information security professionals.Various DLP tools discover where confidential, sensitive, and/orpersonal information is stored and use various techniques toautomatically discover sensitive data within a particular computersystem—for example, in emails, on a particular network, in databases,etc. DLP tools can detect the data, determine a data type for the data,determine the amount of the data, and determine whether the data isencrypted. This may be valuable for security professionals, but thesetools are typically not useful for privacy professionals because thetools typically cannot detect certain privacy attributes that arerequired to be known to determine whether an organization is incompliance with particular privacy policies.

For example, traditional DLP tools cannot typically answer the followingquestions:

-   -   Who was the data collected from (data subject)?    -   Where are those subjects located?    -   Are they minors?    -   How was consent to use the data received?    -   What is the use of the data?    -   Is the use consistent with the use specified at the time of        consent?    -   What country is the data stored in and/or transferred to?

In various embodiments, the system is adapted to integrate withappropriate DLP and/or data discovery tools (e.g., INFORMATICA) and, inresponse to data being discovered by those tools, to show each area ofdata that is discovered as a line-item on a system screen viaintegration. The system may do this, for example, in a manner that issimilar to pending transactions in a checking account that have not yetbeen reconciled.

A designated privacy officer may then select one of those—and eithermatch it up (e.g., reconcile it) with an existing data flow or campaignin the system OR trigger a new assessment to be done on that data tocapture the privacy attributes and data flow.

More Detailed Discussion

Various embodiments of the systems and methods outlined above in regardto this section will now be discussed in greater detail. In particularembodiments, the process begins by integrating a privacy managementsystem with one or more data loss prevention (DLP) software tools and/orone or more data discovery software tools. Such DLP tools may include,for example, CA DataMinder by CA Technologies DLP, TrueDLP by Code GreenNetworks, McAfee Total Protection for Data Loss Prevention by IntelSecurity, or any other suitable DLP tools. Suitable data discoverysoftware tools may include, for example, Sisense, Domo, IBM CognosAnalytics, Looker, Sage Live, or any other suitable data discoverytools. The integration of the privacy management system with the one ormore data loss prevention (DLP) software tools and/or the one or moredata discovery software tools may be accomplished by, for example,establishing communications between the privacy management system andthe one or more data loss prevention (DLP) software tools and/or the oneor more data discovery software tools via one or more suitableapplication programming interfaces (API's). Other embodiments may useany other suitable techniques for integrating the software applicationsand/or systems.

Next, the one or more DLP tools and/or one or more data discovery toolsidentify particular sensitive data stored within computer memory (e.g.,in the memory of a legacy computer system of an organization that isusing the privacy management system to manage its sensitive data). Next,at least partially in response to identifying the particular sensitivedata, the system electronically transmits an electronic notification tothe privacy management system indicating that the sensitive data hasbeen identified. The system then, at least partially in response to theprivacy management system receiving the electronic notification,presents at least a portion of the sensitive data to a user. As anexample, if the system identifies a particular home address, the systemmay display, or otherwise communicate, the home address to the user.Similarly, if the system identifies a particular phone number, thesystem may display the phone number to the user.

The system may present the sensitive data to a user in any suitable wayand/or format. For example, in a particular embodiment, the system maypresent the sensitive information as a selectable or non-selectableentry in a listing on a display screen of other sensitive data alongwith, for example, respective input fields or input objects for eachrespective listing of sensitive data. Such respective inputfields/objects may include, for example, a dropdown menu for allowingthe user to input data regarding the sensitive data.

Next, after presenting the at least a portion of the sensitive data tothe user, the system may prompt the user to indicate whether thesensitive data is data that is currently included in one or more datarecords for a privacy campaign that is currently managed by the privacymanagement system. For example, in the example above, the system maydisplay the identified phone number to the user and prompt the user toindicate whether the identified home number is already associated with adata map for a particular privacy campaign that is currently managed bythe system. To facilitate the answer to this question, the system may,for example, before or after displaying the sensitive information to theuser, automatically search the system's memory to determine whether theidentified home number is already associated with a data map for aparticular privacy campaign that is currently managed by the system. Inthe embodiment described above (which may require manual verification ofthe presence of the sensitive data in the privacy management system),the system may use this information to assist the user in completingthis manual process by, for example: (1) displaying a message indicatingthat the system identified the sensitive data in a particular data map;and/or (2) displaying other data (e.g., related to the identifiedsensitive data) that was obtained from the particular data map. The usermay then use this displayed information to answer the question.

In various embodiments, if the system receives an indication, from theuser, that the sensitive data is data that is currently included in oneor more data records for a privacy campaign that is currently managed bythe privacy management system, the system reconciles the sensitive datawith an existing data flow for the particular privacy campaign. Thesystem may do this, for example by determining whether all relevant dataidentified along with the sensitive data, from memory, is represented inthe system's existing data flow. If so, the system may take any suitableaction to indicate that the sensitive data has been processed and/orthat no further action need be taken. Such actions may include, forexample: (1) updating an electronic log to indicate that processing ofthe identified sensitive data is complete; (2) removing the entry forthe sensitive data from the user's list of sensitive data to beprocessed (which is discussed above); and/or (3) saving an indication,to memory, that the sensitive data has been appropriately processed.

On the other hand, if the system receives an indication, from the user,that the sensitive data is not data that is currently included in one ormore data records for a privacy campaign that is currently managed bythe privacy management system, the system may, for example: (1) initiatea new privacy risk assessment (e.g., a privacy impact assessment) for aparticular privacy campaign to which the sensitive data pertains; (2)obtain, as part of the new privacy risk assessment, one or more privacyattributes of the particular privacy campaign; and (3) save the one ormore privacy attributes of the particular privacy campaign to computermemory. In doing this, the system may, for example, create a new datamap for the identified sensitive data.

It should be understood that the system may be adapted to execute any ofa variety of variations of the functionality discussed above. Forexample, in particular embodiments, the system may be adapted to notrequire manual input in order to reconcile the identified sensitive datawith one or more data records for a privacy campaign that is currentlymanaged by the privacy management system. Rather, the system may, forexample, be adapted to conduct this reconciliation automatically ifcertain criteria are met (e.g., there is an exact match between at leasta portion of the sensitive data and data that is already stored in theone or more system data records). In particular embodiments, the systemmay be adapted to allow particular organizations to customize thisfunctionality based on one or more system settings.

It should also be understood that, although the above functionality isdescribed, in various examples, in regard to data mapping, otherembodiments may be adapted to facilitate the reconciliation of sensitivedata identified using DLP tools and/or data discovery tools with anysuitable data structures that are managed by, or otherwise accessed by,privacy management software that, for example, is integrated with thesetools. Various embodiments may be used to reconcile data other than datamapping data with any suitable data structure, including any datastructures that are managed by, or otherwise accessed by, the privacymanagement software. It should also be understood that the references,herein, to a privacy management system refers, for example, to acomputer system having at least one computer processor and associatedmemory executing privacy management software.

6. Privacy Policy Compliance System that Allows Users to Attach Emailsto Individual Campaigns.

Privacy officers frequently receive emails (or other electronicmessages) that are associated with an existing privacy assessment orcampaign, or a potential future privacy assessment. For record keepingand auditing purposes, the privacy officer may wish to maintain thoseemails in a central storage location, and not in email. In variousembodiments, the system is adapted to allow users to automaticallyattach the email to an existing privacy assessment, data flow, and/orprivacy campaign. Alternatively, or additionally, the system may allow auser to automatically store emails within a data store associated withthe system, and to store the emails as “unassigned”, so that they maylater be assigned to an existing privacy assessment, data flow, and/orprivacy campaign.

-   -   In various embodiments, the system is adapted to allow a user to        store an email using:        -   a browser plugin-extension that captures webmail;        -   a Plug-in directly with office 365 or google webmail (or            other suitable email application);        -   a Plug-in with email clients on computers such as Outlook;        -   via an integrated email alias that the email is forwarded            to; or        -   any other suitable configuration

7. Various Aspects of Related Mobile Applications

In particular embodiments, the system may use a mobile app (e.g., thatruns on a particular mobile device associated by a user) to collect datafrom a user. The mobile app may be used, for example, to collect answersto screening questions. The app may also be adapted to allow users toeasily input data documenting and/or reporting a privacy incident. Forexample, the app may be adapted to assist a user in using their mobiledevice to capture an image of a privacy incident (e.g., a screen shotdocumenting that data has been stored in an improper location, or that aprintout of sensitive information has been left in a public workspacewithin an organization.)

The mobile app may also be adapted to provide incremental training toindividuals. For example, the system may be adapted to provideincremental training to a user (e.g., in the form of the presentation ofshort lessons on privacy). Training sessions may be followed by shortquizzes that are used to allow the user to assess their understanding ofthe information and to confirm that they have completed the training.

8. Automatic Generation of Personal Data Inventory for Organization

In particular embodiments, the system is adapted to generate and displayan inventory of the personal data that an organization collects andstores within its systems (or other systems). As discussed above, invarious embodiments, the system is adapted to conduct privacy impactassessments for new and existing privacy campaigns. During a privacyimpact assessment for a particular privacy campaign, the system may askone or more users a series of privacy impact assessment questionsregarding the particular privacy campaign and then store the answers tothese questions in the system's memory, or in memory of another system,such a third-party computer server.

Such privacy impact assessment questions may include questionsregarding: (1) what type of data is to be collected as part of thecampaign; (2) who the data is to be collected from; (3) where the datais to be stored; (4) who will have access to the data; (5) how long thedata will be kept before being deleted from the system's memory orarchived; and/or (6) any other relevant information regarding thecampaign.

The system may store the above information, for example, in any suitabledata structure, such as a database. In particular embodiments, thesystem may be configured to selectively (e.g., upon request by anauthorized user) generate and display a personal data inventory for theorganization that includes, for example, all of the organization'scurrent active campaigns, all of the organization's current and pastcampaigns, or any other listing of privacy campaigns that, for example,satisfy criteria specified by a user. The system may be adapted todisplay and/or export the data inventory in any suitable format (e.g.,in a table, a spreadsheet, or any other suitable format).

9. Integrated/Automated Solution for Privacy Risk Assessments

Continuing with Concept 9, above, in various embodiments, the system mayexecute multiple integrated steps to generate a personal data inventoryfor a particular organization. For example, in a particular embodiment,the system first conducts a Privacy Threshold Assessment (PTA) by askinga user a relatively short set of questions (e.g., between 1 and 15questions) to quickly determine whether the risk associated with thecampaign may potentially exceed a pre-determined risk threshold (e.g.,whether the campaign is a potentially high-risk campaign). The systemmay do this, for example, by using any of the above techniques to assigna collective risk score to the user's answers to the questions anddetermining whether the collective risk score exceeds a particular riskthreshold value. Alternatively, the system may be configured todetermine that the risk associated with the campaign exceeds the riskthreshold value if the user answers a particular one or more of thequestions in a certain way.

The system may be configured for, in response to the user's answers toone or more of the questions within the Privacy Threshold Assessmentindicating that the campaign exceeds, or may potentially exceed, apre-determined risk threshold, presenting the user with a longer set ofdetailed questions regarding the campaign (e.g., a Privacy ImpactAssessment). The system may then use the user's answers to this longerlist of questions to assess the overall risk of the campaign, forexample, as described above.

In particular embodiments, the system may be configured for, in responseto the user's answers to one or more of the questions within the PrivacyThreshold Assessment indicating that the campaign does not exceed, ordoes not potentially exceed, a pre-determined risk threshold, notpresenting the user with a longer set of detailed questions regardingthe campaign (e.g., a Privacy Impact Assessment). In such a case, thesystem may simply save an indication to memory that the campaign is arelatively low risk campaign.

Accordingly, in particular embodiments, the system may be adapted toautomatically initiate a Privacy Impact Assessment if the results of ashorter Privacy Threshold Assessment satisfy certain criteria.Additionally, or alternatively, in particular embodiments, the systemmay be adapted to allow a privacy officer to manually initiate a PrivacyImpact Assessment for a particular campaign.

In particular embodiments, built into the Privacy Threshold Assessmentand the Privacy Impact Assessment are the data mapping questions and/orsub-questions of how the personal data obtained through the campaignwill be collected, used, stored, accessed, retained, and/or transferred,etc. In particular embodiments: (1) one or more of these questions areasked in the Privacy Threshold Assessment; and (2) one or more of thequestions are asked in the Privacy Impact Assessment. In suchembodiments, the system may obtain the answers to each of thesequestions, as captured during the Privacy Threshold Assessment and thePrivacy Impact Assessment, and then use the respective answers togenerate the end-to-end data flow for the relevant privacy campaign.

The system may then link all of the data flows across all of theorganization's privacy campaigns together in order to show a completeevergreen version of the personal data inventory of the organization.Thus, the system may efficiently generate the personal data inventory ofan organization (e.g., through the use of reduced computer processingpower) by automatically gathering the data needed to prepare thepersonal data inventory while conducting Privacy Threshold Assessmentsand Privacy Impact Assessments.

System for Preventing Individuals from Trying to Game the System

As discussed above, in particular embodiments, the system is adapted todisplay a series of threshold questions for particular privacy campaignsand to use conditional logic to assess whether to present additional,follow-up questions to the user. There may be situations in which a usermay answer, or attempt to answer, one or more of the threshold questionsincorrectly (e.g., dishonestly) in an attempt to avoid needing to answeradditional questions. This type of behavior can present seriouspotential problems for the organization because the behavior may resultin privacy risks associated with a particular privacy campaign beinghidden due to the incorrect answer or answers.

To address this issue, in various embodiments, the system: (1) maintainsa historical record of every button press (e.g., un-submitted systeminput) that an individual makes when a question is presented to them;and (2) tracks, and saves to memory, each incidence of the individualchanging their answer to a question (e.g., (a) before formallysubmitting the answer by pressing an “enter” key, or other “submit” keyon a user interface, such as a keyboard or graphical user interface on atouch-sensitive display screen; or (b) after initially submitting theanswer).

The system may also be adapted to automatically determine whether aparticular question (e.g., threshold question) is a “critical” questionthat, if answered in a certain way, would cause the conditional logictrigger to present the user with one or more follow-up questions. Forexample, the system may, in response to receiving the user's full set ofanswers to the threshold questions, automatically identify anyindividual question within the series of threshold questions that, ifanswered in a particular way (e.g., differently than the user answeredthe question) would have caused the system to display one or more followup questions. The system may then flag those identified questions, inthe system's memory, as “critical” questions.

Alternatively, the system may be adapted to allow a user (e.g., aprivacy officer of an organization) who is drafting a particularthreshold question that, when answered in a particular way, willautomatically trigger the system to display one or more follow upquestions to the user, to indicate that is a “critical” thresholdquestion. The system may then save this “critical” designation of thequestion to the system's computer memory.

In various embodiments, the system is configured, for any questions thatare deemed “critical” (e.g., either by the system, or manually, asdiscussed above), to determine whether the user exhibited any abnormalbehavior when answering the question. For example, the system may checkto see whether the user changed their answer once, or multiple times,before submitting their answer to the question (e.g., by tracking theuser's keystrokes while they are answering the threshold question, asdescribed above). As another example, the system may determine whetherit took the user longer than a pre-determined threshold amount of time(e.g., 5 minutes, 3 minutes, etc.) to answer the critical thresholdquestion.

In particular embodiments, the system may be adapted, in response todetermining that the user exhibited abnormal behavior when answering thecritical threshold question, to automatically flag the thresholdquestion and the user's answer to that question for later follow up by adesignated individual or team (e.g., a member of the organization'sprivacy team). In particular embodiments, the system may also, oralternatively, be adapted to automatically generate and transmit amessage to one or more individuals (e.g., the organization's chiefprivacy officer) indicating that the threshold question may have beenanswered incorrectly and that follow-up regarding the question may beadvisable. After receiving the message, the individual may, inparticular embodiments, follow up with the individual who answered thequestion, or conduct other additional research, to determine whether thequestion was answered accurately.

CONCLUSION

Although embodiments above are described in reference to various systemsand methods for creating and managing data flows related to individualprivacy campaigns, it should be understood that various aspects of thesystem described above may be applicable to other privacy-relatedsystems, or to other types of systems, in general. For example, thefunctionality described above for obtaining the answers to variousquestions (e.g., assigning individual questions or sections of questionsto multiple different users, facilitating collaboration between theusers as they complete the questions, automatically reminding users tocomplete their assigned questions, and other aspects of the systems andmethods described above) may be used within the context of PrivacyImpact Assessments (e.g., in having users answer certain questions todetermine whether a certain project complies with an organization'sprivacy policies).

While this specification contains many specific embodiment details,these should not be construed as limitations on the scope of anyinvention or of what may be claimed, but rather as descriptions offeatures that may be specific to particular embodiments of particularinventions. Certain features that are described in this specification inthe context of separate embodiments may also be implemented incombination in a single embodiment. Conversely, various features thatare described in the context of a single embodiment may also beimplemented in multiple embodiments separately or in any suitablesub-combination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination may in some cases be excisedfrom the combination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems maygenerally be integrated together in a single software product orpackaged into multiple software products.

Many modifications and other embodiments of the invention will come tomind to one skilled in the art to which this invention pertains havingthe benefit of the teachings presented in the foregoing descriptions andthe associated drawings. While examples discussed above cover the use ofvarious embodiments in the context of operationalizing privacycompliance and assessing risk of privacy campaigns, various embodimentsmay be used in any other suitable context. Therefore, it is to beunderstood that the invention is not to be limited to the specificembodiments disclosed and that modifications and other embodiments areintended to be included within the scope of the appended claims.Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for the purposes of limitation.

What is claimed is:
 1. A method comprising: identifying, by computinghardware, a plurality of pieces of data associated with a data subjectin a data map; determining, by the computing hardware, that theplurality of pieces of data comprise sensitive data; determining, by thecomputing hardware, that a first portion of the sensitive data exactlymatches privacy campaign data stored in a privacy campaign data recordfor a data processing activity; and reconciling, by the computinghardware based on determining that the first portion of the sensitivedata exactly matches the privacy campaign data, the plurality of piecesof data with a data flow for the data processing activity by:determining whether each of the plurality of pieces of data isrepresented in the data flow; in response to determining that at leastone of the plurality of pieces of data is not represented in the dataflow, updating the data flow by associating the at least one of theplurality of pieces of data with the data flow; and defining, in thedata flow, a privacy related attribute for the at least one of theplurality of pieces of data, the privacy related attribute including anindication of the data subject.
 2. The method of claim 1, furthercomprising: facilitating, by the computing hardware using the data flow,performance of network operations for retrieving data responsive to aquery related to one or more data repositories identified in the dataflow, the query including a request to identify personal data associatedwith the data subject.
 3. The method of claim 1, wherein: reconcilingthe plurality of pieces of data with the data flow for the processingactivity further comprises: generating a user interface comprising arespective interactive element for each of the plurality of pieces ofdata; providing the user interface for display on a computing device;and receiving, via each respective interactive element, an indication ofan inclusion status of each of the plurality of pieces of data in thedata flow; and determining whether each of the plurality of pieces ofdata is represented in the data flow comprises determining whether eachof the plurality of pieces of data is represented in the data flow basedon the indication of the inclusion status.
 4. The method of claim 2,further comprising in response to determining that at least one of theplurality of pieces of data is not represented in the data flow,initiating a risk assessment for the data processing activity.
 5. Themethod of claim 1, further comprising: generating, by the computinghardware, a graphical user interface that comprises a visualrepresentation of the data flow by: configuring a first visualindication of a first data asset in the data flow, configuring a secondvisual indication of a second data asset in the data flow, configuring athird visual indication of an exchange of the at least one of theplurality of pieces of data between the first data asset and the seconddata asset based on the data flow; and providing, by the computinghardware, the graphical user interface for display on a computingdevice.
 6. The method of claim 5, wherein: the method further comprisesdetermining, by the computing hardware, an encryption status of the atleast one of the plurality of pieces of data; and the third visualindication reflects the encryption status.
 7. The method of claim 1further comprising modifying, by the computing hardware, the encryptionstatus of the at least one of the plurality of pieces of data inresponse to determining that the at least one of the plurality of piecesof data is not represented in the data flow.
 8. A system comprising: anon-transitory computer-readable medium storing instructions; and aprocessing device communicatively coupled to the non-transitorycomputer-readable medium, wherein, the processing device is configuredto execute the instructions and thereby perform operations comprising:identifying a plurality of pieces of data associated with a data subjectin a data map; determining that the plurality of pieces of data comprisesensitive data; determining that a first portion of the sensitive dataexactly matches privacy campaign data stored in a privacy campaign datarecord for a data processing activity; and reconciling, based ondetermining that the first portion of the sensitive data exactly matchesthe privacy campaign data, the plurality of pieces of data with a dataflow for the data processing activity by: determining whether each ofthe plurality of pieces of data is represented in the data flow; inresponse to determining that at least one of the plurality of pieces ofdata is not represented in the data flow, updating the data flow byassociating the at least one of the plurality of pieces of data with thedata flow; and defining, in the data flow, a privacy related attributefor the at least one of the plurality of pieces of data, the privacyrelated attribute including an indication of the data subject.
 9. Thesystem of claim 8, wherein the operations further comprise facilitating,using the data flow, performance of network operations for retrievingdata responsive to a query related to one or more data repositoriesidentified in the data flow, the query including a request to identifypersonal data associated with the data subject.
 10. The system of claim8, wherein: reconciling the plurality of pieces of data with the dataflow for the processing activity further comprises: generating a userinterface comprising a respective interactive element for each of theplurality of pieces of data; providing the user interface for display ona computing device; and receiving, via each respective interactiveelement, an indication of an inclusion status of each of the pluralityof pieces of data in the data flow; and determining whether each of theplurality of pieces of data is represented in the data flow comprisesdetermining whether each of the plurality of pieces of data isrepresented in the data flow based on the indication of the inclusionstatus.
 11. The system of claim 8, wherein the operations furthercomprise, in response to determining that at least one of the pluralityof pieces of data is not represented in the data flow, initiating a riskassessment for the data processing activity.
 12. The system of claim 8,wherein the operations further comprise defining at least a secondprivacy related attribute for the at least one of the plurality ofpieces of data based on data responsive to the risk assessment for thedata processing activity.
 13. The system of claim 8, wherein theoperations further comprise: generating a graphical user interface thatcomprises a visual representation of the data flow by: configuring afirst visual indication of a first data asset in the data flow,configuring a second visual indication of a second data asset in thedata flow, configuring a third visual indication of an exchange of theat least one of the plurality of pieces of data between the first dataasset and the second data asset based on the data flow; and providingthe graphical user interface for display on a computing device.
 14. Thesystem of claim 8, wherein: the operations further comprise determiningan encryption status of the at least one of the plurality of pieces ofdata; and the third visual indication reflects the encryption status.15. The system of claim 8, wherein the operations further comprisemodifying the encryption status of the at least one of the plurality ofpieces of data in response to determining that the at least one of theplurality of pieces of data is not represented in the data flow.
 16. Anon-transitory computer-readable medium having program code that isstored thereon, the program code executable by one or more processingdevices for performing operations comprising: identifying a plurality ofpieces of data associated with a data subject in a data map; determiningthat the plurality of pieces of data comprise sensitive data;determining that a first portion of the sensitive data exactly matchesprivacy campaign data stored in a privacy campaign data record for adata processing activity; and reconciling, based on determining that thefirst portion of the sensitive data exactly matches the privacy campaigndata, the plurality of pieces of data with a data flow for the dataprocessing activity by: determining whether each of the plurality ofpieces of data is represented in the data flow; in response todetermining that at least one of the plurality of pieces of data is notrepresented in the data flow, updating the data flow by associating theat least one of the plurality of pieces of data with the data flow; anddefining, in the data flow, a privacy related attribute for the at leastone of the plurality of pieces of data, the privacy related attributeincluding an indication of the data subject.
 17. The non-transitorycomputer-readable medium of claim 16, wherein: reconciling the pluralityof pieces of data with the data flow for the processing activity furthercomprises: generating a user interface comprising a respectiveinteractive element for each of the plurality of pieces of data;providing the user interface for display on a computing device; andreceiving, via each respective interactive element, an indication of aninclusion status of each of the plurality of pieces of data in the dataflow; and determining whether each of the plurality of pieces of data isrepresented in the data flow comprises determining whether each of theplurality of pieces of data is represented in the data flow based on theindication of the inclusion status.
 18. The non-transitorycomputer-readable medium of claim 16, wherein the operations furthercomprise, in response to determining that at least one of the pluralityof pieces of data is not represented in the data flow, initiating a riskassessment for the data processing activity.
 19. The non-transitorycomputer-readable medium of claim 16, wherein the operations furthercomprise defining at least a second privacy related attribute for the atleast one of the plurality of pieces of data based on data responsive tothe risk assessment for the data processing activity.
 20. Thenon-transitory computer-readable medium of claim 16, wherein theoperations further comprise: generating a graphical user interface thatcomprises a visual representation of the data flow by: configuring afirst visual indication of a first data asset in the data flow,configuring a second visual indication of a second data asset in thedata flow, configuring a third visual indication of an exchange of theat least one of the plurality of pieces of data between the first dataasset and the second data asset based on the data flow; and providingthe graphical user interface for display on a computing device.